├── .gitignore ├── LICENSE ├── README.md ├── alphabet.json ├── data ├── ag_news_csv │ ├── classes.txt │ ├── readme.txt │ ├── test.csv │ └── train.csv └── names │ ├── Arabic.txt │ ├── Chinese.txt │ ├── Czech.txt │ ├── Dutch.txt │ ├── English.txt │ ├── French.txt │ ├── German.txt │ ├── Greek.txt │ ├── Irish.txt │ ├── Italian.txt │ ├── Japanese.txt │ ├── Korean.txt │ ├── Polish.txt │ ├── Portuguese.txt │ ├── Russian.txt │ ├── Scottish.txt │ ├── Spanish.txt │ └── Vietnamese.txt ├── data_loader.py ├── data_loader_txt.py ├── metric.py ├── model.py ├── model_CharCNN2D.py ├── model_SentCNN.py ├── mydatasets.py ├── predict.py ├── test.py └── train.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | env/ 12 | build/ 13 | develop-eggs/ 14 | dist/ 15 | downloads/ 16 | eggs/ 17 | .eggs/ 18 | lib/ 19 | lib64/ 20 | parts/ 21 | sdist/ 22 | var/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | 27 | # PyInstaller 28 | # Usually these files are written by a python script from a template 29 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 30 | *.manifest 31 | *.spec 32 | 33 | # Installer logs 34 | pip-log.txt 35 | pip-delete-this-directory.txt 36 | 37 | # Unit test / coverage reports 38 | htmlcov/ 39 | .tox/ 40 | .coverage 41 | .coverage.* 42 | .cache 43 | nosetests.xml 44 | coverage.xml 45 | *,cover 46 | .hypothesis/ 47 | 48 | # Translations 49 | *.mo 50 | *.pot 51 | 52 | # Django stuff: 53 | *.log 54 | local_settings.py 55 | 56 | # Flask stuff: 57 | instance/ 58 | .webassets-cache 59 | 60 | # Scrapy stuff: 61 | .scrapy 62 | 63 | # Sphinx documentation 64 | docs/_build/ 65 | 66 | # PyBuilder 67 | target/ 68 | 69 | # IPython Notebook 70 | .ipynb_checkpoints 71 | 72 | # pyenv 73 | .python-version 74 | 75 | # celery beat schedule file 76 | celerybeat-schedule 77 | 78 | # dotenv 79 | .env 80 | 81 | # virtualenv 82 | venv/ 83 | ENV/ 84 | 85 | # Spyder project settings 86 | .spyderproject 87 | 88 | # Rope project settings 89 | .ropeproject 90 | 91 | # Mac 92 | .DS_Store 93 | 94 | # model cache 95 | *.pt 96 | 97 | # dataset 98 | rt-polaritydata 99 | trees 100 | *.tar 101 | *.zip 102 | 103 | # pycharm 104 | .idea 105 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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SGD|Adam|ASGD are supported 52 | [default: Adam] 53 | --class_weight Weights should be a 1D Tensor assigning weight to each 54 | of the classes. 55 | --dynamic_lr Use dynamic learning schedule. 56 | --milestones MILESTONES [MILESTONES ...] 57 | List of epoch indices. Must be increasing. 58 | Default:[5,10,15] 59 | --decay_factor DECAY_FACTOR 60 | Decay factor for reducing learning rate [default: 0.5] 61 | 62 | Model options: 63 | --alphabet_path ALPHABET_PATH 64 | Contains all characters for prediction 65 | --l0 L0 maximum length of input sequence to CNNs [default: 66 | 1014] 67 | --shuffle shuffle the data every epoch 68 | --dropout DROPOUT the probability for dropout [default: 0.5] 69 | -kernel_num KERNEL_NUM 70 | number of each kind of kernel 71 | -kernel_sizes KERNEL_SIZES 72 | comma-separated kernel size to use for convolution 73 | 74 | Device options: 75 | --num_workers NUM_WORKERS 76 | Number of workers used in data-loading 77 | --cuda enable the gpu 78 | 79 | Experiment options: 80 | --verbose Turn on progress tracking per iteration for debugging 81 | --continue_from CONTINUE_FROM 82 | Continue from checkpoint model 83 | --checkpoint Enables checkpoint saving of model 84 | --checkpoint_per_batch CHECKPOINT_PER_BATCH 85 | Save checkpoint per batch. 0 means never save 86 | [default: 10000] 87 | --save_folder SAVE_FOLDER 88 | Location to save epoch models, training configurations 89 | and results. 90 | --log_config Store experiment configuration 91 | --log_result Store experiment result 92 | --log_interval LOG_INTERVAL 93 | how many steps to wait before logging training status 94 | [default: 1] 95 | --val_interval VAL_INTERVAL 96 | how many steps to wait before vaidation [default: 200] 97 | --save_interval SAVE_INTERVAL 98 | how many epochs to wait before saving [default:1] 99 | ``` 100 | 101 | 102 | ``` 103 | python train.py 104 | ``` 105 | You will get: 106 | 107 | ``` 108 | Epoch[8] Batch[200] - loss: 0.237892 lr: 0.00050 acc: 93.7500%(120/128)) 109 | Evaluation - loss: 0.363364 acc: 89.1155%(6730/7552) 110 | Label: 0 Prec: 93.2% (1636/1755) Recall: 86.6% (1636/1890) F-Score: 89.8% 111 | Label: 1 Prec: 94.6% (1802/1905) Recall: 95.6% (1802/1884) F-Score: 95.1% 112 | Label: 2 Prec: 85.6% (1587/1854) Recall: 84.1% (1587/1888) F-Score: 84.8% 113 | Label: 3 Prec: 83.7% (1705/2038) Recall: 90.2% (1705/1890) F-Score: 86.8% 114 | ``` 115 | 116 | ## Test 117 | If you has construct you test set, you make testing like: 118 | 119 | ``` 120 | python test.py --test-path='data/ag_news_csv/test.csv' --model-path='models_CharCNN/CharCNN_best.pth.tar' 121 | ``` 122 | The model-path option means where your model load from. 123 | 124 | 125 | ## Reference 126 | * Xiang Zhang, Junbo Zhao, Yann LeCun. [Character-level Convolutional Networks for Text Classification](http://arxiv.org/abs/1509.01626). Advances in Neural Information Processing Systems 28 (NIPS 2015) 127 | 128 | -------------------------------------------------------------------------------- /alphabet.json: -------------------------------------------------------------------------------- 1 | [ 2 | "a", 3 | "b", 4 | "c", 5 | "d", 6 | "e", 7 | "f", 8 | "g", 9 | "h", 10 | "i", 11 | "j", 12 | "k", 13 | "l", 14 | "m", 15 | "n", 16 | "o", 17 | "p", 18 | "q", 19 | "r", 20 | "s", 21 | "t", 22 | "u", 23 | "v", 24 | "w", 25 | "x", 26 | "y", 27 | "z", 28 | 29 | "0", 30 | "1", 31 | "2", 32 | "3", 33 | "4", 34 | "5", 35 | "6", 36 | "7", 37 | "8", 38 | "9", 39 | 40 | "-", 41 | ",", 42 | ";", 43 | ".", 44 | "!", 45 | "?", 46 | ":", 47 | "'", 48 | "\"", 49 | "\\", 50 | "/", 51 | "|", 52 | "_", 53 | "@", 54 | "#", 55 | "$", 56 | "%", 57 | "^", 58 | "&", 59 | "*", 60 | "~", 61 | "`", 62 | "+", 63 | "-", 64 | "=", 65 | "<", 66 | ">", 67 | "(", 68 | ")", 69 | "[", 70 | "]", 71 | "{", 72 | "}", 73 | "\n" 74 | 75 | ] -------------------------------------------------------------------------------- /data/ag_news_csv/classes.txt: -------------------------------------------------------------------------------- 1 | World 2 | Sports 3 | Business 4 | Sci/Tech 5 | -------------------------------------------------------------------------------- /data/ag_news_csv/readme.txt: -------------------------------------------------------------------------------- 1 | AG's News Topic Classification Dataset 2 | 3 | Version 3, Updated 09/09/2015 4 | 5 | 6 | ORIGIN 7 | 8 | AG is a collection of more than 1 million news articles. News articles have been gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of activity. ComeToMyHead is an academic news search engine which has been running since July, 2004. The dataset is provided by the academic comunity for research purposes in data mining (clustering, classification, etc), information retrieval (ranking, search, etc), xml, data compression, data streaming, and any other non-commercial activity. For more information, please refer to the link http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html . 9 | 10 | The AG's news topic classification dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the dataset above. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). 11 | 12 | 13 | DESCRIPTION 14 | 15 | The AG's news topic classification dataset is constructed by choosing 4 largest classes from the original corpus. Each class contains 30,000 training samples and 1,900 testing samples. The total number of training samples is 120,000 and testing 7,600. 16 | 17 | The file classes.txt contains a list of classes corresponding to each label. 18 | 19 | The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3 columns in them, corresponding to class index (1 to 4), title and description. The title and description are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n". 20 | -------------------------------------------------------------------------------- /data/names/Arabic.txt: -------------------------------------------------------------------------------- 1 | Khoury 2 | Nahas 3 | Daher 4 | Gerges 5 | Nazari 6 | Maalouf 7 | Gerges 8 | Naifeh 9 | Guirguis 10 | Baba 11 | Sabbagh 12 | Attia 13 | Tahan 14 | Haddad 15 | Aswad 16 | Najjar 17 | Dagher 18 | Maloof 19 | Isa 20 | Asghar 21 | Nader 22 | Gaber 23 | Abboud 24 | Maalouf 25 | Zogby 26 | Srour 27 | Bahar 28 | Mustafa 29 | Hanania 30 | Daher 31 | Tuma 32 | Nahas 33 | Saliba 34 | Shamoon 35 | Handal 36 | Baba 37 | Amari 38 | Bahar 39 | Atiyeh 40 | Said 41 | Khouri 42 | Tahan 43 | Baba 44 | Mustafa 45 | Guirguis 46 | Sleiman 47 | Seif 48 | Dagher 49 | Bahar 50 | Gaber 51 | Harb 52 | Seif 53 | Asker 54 | Nader 55 | Antar 56 | Awad 57 | Srour 58 | Shadid 59 | Hajjar 60 | Hanania 61 | Kalb 62 | Shadid 63 | Bazzi 64 | Mustafa 65 | Masih 66 | Ghanem 67 | Haddad 68 | Isa 69 | Antoun 70 | Sarraf 71 | Sleiman 72 | Dagher 73 | Najjar 74 | Malouf 75 | Nahas 76 | Naser 77 | Saliba 78 | Shamon 79 | Malouf 80 | Kalb 81 | Daher 82 | Maalouf 83 | Wasem 84 | Kanaan 85 | Naifeh 86 | Boutros 87 | Moghadam 88 | Masih 89 | Sleiman 90 | Aswad 91 | Cham 92 | Assaf 93 | Quraishi 94 | Shalhoub 95 | Sabbag 96 | Mifsud 97 | Gaber 98 | Shammas 99 | Tannous 100 | Sleiman 101 | Bazzi 102 | Quraishi 103 | Rahal 104 | Cham 105 | Ghanem 106 | Ghanem 107 | Naser 108 | Baba 109 | Shamon 110 | Almasi 111 | Basara 112 | Quraishi 113 | Bata 114 | Wasem 115 | Shamoun 116 | Deeb 117 | Touma 118 | Asfour 119 | Deeb 120 | Hadad 121 | Naifeh 122 | Touma 123 | Bazzi 124 | Shamoun 125 | Nahas 126 | Haddad 127 | Arian 128 | Kouri 129 | Deeb 130 | Toma 131 | Halabi 132 | Nazari 133 | Saliba 134 | Fakhoury 135 | Hadad 136 | Baba 137 | Mansour 138 | Sayegh 139 | Antar 140 | Deeb 141 | Morcos 142 | Shalhoub 143 | Sarraf 144 | Amari 145 | Wasem 146 | Ganim 147 | Tuma 148 | Fakhoury 149 | Hadad 150 | Hakimi 151 | Nader 152 | Said 153 | Ganim 154 | Daher 155 | Ganem 156 | Tuma 157 | Boutros 158 | Aswad 159 | Sarkis 160 | Daher 161 | Toma 162 | Boutros 163 | Kanaan 164 | Antar 165 | Gerges 166 | Kouri 167 | Maroun 168 | Wasem 169 | Dagher 170 | Naifeh 171 | Bishara 172 | Ba 173 | Cham 174 | Kalb 175 | Bazzi 176 | Bitar 177 | Hadad 178 | Moghadam 179 | Sleiman 180 | Shamoun 181 | Antar 182 | Atiyeh 183 | Koury 184 | Nahas 185 | Kouri 186 | Maroun 187 | Nassar 188 | Sayegh 189 | Haik 190 | Ghanem 191 | Sayegh 192 | Salib 193 | Cham 194 | Bata 195 | Touma 196 | Antoun 197 | Antar 198 | Bata 199 | Botros 200 | Shammas 201 | Ganim 202 | Sleiman 203 | Seif 204 | Moghadam 205 | Ba 206 | Tannous 207 | Bazzi 208 | Seif 209 | Salib 210 | Hadad 211 | Quraishi 212 | Halabi 213 | Essa 214 | Bahar 215 | Kattan 216 | Boutros 217 | Nahas 218 | Sabbagh 219 | Kanaan 220 | Sayegh 221 | Said 222 | Botros 223 | Najjar 224 | Toma 225 | Bata 226 | Atiyeh 227 | Halabi 228 | Tannous 229 | Kouri 230 | Shamoon 231 | Kassis 232 | Haddad 233 | Tuma 234 | Mansour 235 | Antar 236 | Kassis 237 | Kalb 238 | Basara 239 | Rahal 240 | Mansour 241 | Handal 242 | Morcos 243 | Fakhoury 244 | Hadad 245 | Morcos 246 | Kouri 247 | Quraishi 248 | Almasi 249 | Awad 250 | Naifeh 251 | Koury 252 | Asker 253 | Maroun 254 | Fakhoury 255 | Sabbag 256 | Sarraf 257 | Shamon 258 | Assaf 259 | Boutros 260 | Malouf 261 | Nassar 262 | Qureshi 263 | Ghanem 264 | Srour 265 | Almasi 266 | Qureshi 267 | Ghannam 268 | Mustafa 269 | Najjar 270 | Kassab 271 | Shadid 272 | Shamoon 273 | Morcos 274 | Atiyeh 275 | Isa 276 | Ba 277 | Baz 278 | Asker 279 | Seif 280 | Asghar 281 | Hajjar 282 | Deeb 283 | Essa 284 | Qureshi 285 | Abboud 286 | Ganem 287 | Haddad 288 | Koury 289 | Nassar 290 | Abadi 291 | Toma 292 | Tannous 293 | Harb 294 | Issa 295 | Khouri 296 | Mifsud 297 | Kalb 298 | Gaber 299 | Ganim 300 | Boulos 301 | Samaha 302 | Haddad 303 | Sabbag 304 | Wasem 305 | Dagher 306 | Rahal 307 | Atiyeh 308 | Antar 309 | Asghar 310 | Mansour 311 | Awad 312 | Boulos 313 | Sarraf 314 | Deeb 315 | Abadi 316 | Nazari 317 | Daher 318 | Gerges 319 | Shamoon 320 | Gaber 321 | Amari 322 | Sarraf 323 | Nazari 324 | Saliba 325 | Naifeh 326 | Nazari 327 | Hakimi 328 | Shamon 329 | Abboud 330 | Quraishi 331 | Tahan 332 | Safar 333 | Hajjar 334 | Srour 335 | Gaber 336 | Shalhoub 337 | Attia 338 | Safar 339 | Said 340 | Ganem 341 | Nader 342 | Asghar 343 | Mustafa 344 | Said 345 | Antar 346 | Botros 347 | Nader 348 | Ghannam 349 | Asfour 350 | Tahan 351 | Mansour 352 | Attia 353 | Touma 354 | Najjar 355 | Kassis 356 | Abboud 357 | Bishara 358 | Bazzi 359 | Shalhoub 360 | Shalhoub 361 | Safar 362 | Khoury 363 | Nazari 364 | Sabbag 365 | Sleiman 366 | Atiyeh 367 | Kouri 368 | Bitar 369 | Zogby 370 | Ghanem 371 | Assaf 372 | Abadi 373 | Arian 374 | Shalhoub 375 | Khoury 376 | Morcos 377 | Shamon 378 | Wasem 379 | Abadi 380 | Antoun 381 | Baz 382 | Naser 383 | Assaf 384 | Saliba 385 | Nader 386 | Mikhail 387 | Naser 388 | Daher 389 | Morcos 390 | Awad 391 | Nahas 392 | Sarkis 393 | Malouf 394 | Mustafa 395 | Fakhoury 396 | Ghannam 397 | Shadid 398 | Gaber 399 | Koury 400 | Atiyeh 401 | Shamon 402 | Boutros 403 | Sarraf 404 | Arian 405 | Fakhoury 406 | Abadi 407 | Kassab 408 | Nahas 409 | Quraishi 410 | Mansour 411 | Samaha 412 | Wasem 413 | Seif 414 | Fakhoury 415 | Saliba 416 | Cham 417 | Bahar 418 | Shamoun 419 | Essa 420 | Shamon 421 | Asfour 422 | Bitar 423 | Cham 424 | Tahan 425 | Tannous 426 | Daher 427 | Khoury 428 | Shamon 429 | Bahar 430 | Quraishi 431 | Ghannam 432 | Kassab 433 | Zogby 434 | Basara 435 | Shammas 436 | Arian 437 | Sayegh 438 | Naifeh 439 | Mifsud 440 | Sleiman 441 | Arian 442 | Kassis 443 | Shamoun 444 | Kassis 445 | Harb 446 | Mustafa 447 | Boulos 448 | Asghar 449 | Shamon 450 | Kanaan 451 | Atiyeh 452 | Kassab 453 | Tahan 454 | Bazzi 455 | Kassis 456 | Qureshi 457 | Basara 458 | Shalhoub 459 | Sayegh 460 | Haik 461 | Attia 462 | Maroun 463 | Kassis 464 | Sarkis 465 | Harb 466 | Assaf 467 | Kattan 468 | Antar 469 | Sleiman 470 | Touma 471 | Sarraf 472 | Bazzi 473 | Boulos 474 | Baz 475 | Issa 476 | Shamon 477 | Shadid 478 | Deeb 479 | Sabbag 480 | Wasem 481 | Awad 482 | Mansour 483 | Saliba 484 | Fakhoury 485 | Arian 486 | Bishara 487 | Dagher 488 | Bishara 489 | Koury 490 | Fakhoury 491 | Naser 492 | Nader 493 | Antar 494 | Gerges 495 | Handal 496 | Hanania 497 | Shadid 498 | Gerges 499 | Kassis 500 | Essa 501 | Assaf 502 | Shadid 503 | Seif 504 | Shalhoub 505 | Shamoun 506 | Hajjar 507 | Baba 508 | Sayegh 509 | Mustafa 510 | Sabbagh 511 | Isa 512 | Najjar 513 | Tannous 514 | Hanania 515 | Ganem 516 | Gerges 517 | Fakhoury 518 | Mifsud 519 | Nahas 520 | Bishara 521 | Bishara 522 | Abadi 523 | Sarkis 524 | Masih 525 | Isa 526 | Attia 527 | Kalb 528 | Essa 529 | Boulos 530 | Basara 531 | Halabi 532 | Halabi 533 | Dagher 534 | Attia 535 | Kassis 536 | Tuma 537 | Gerges 538 | Ghannam 539 | Toma 540 | Baz 541 | Asghar 542 | Zogby 543 | Aswad 544 | Hadad 545 | Dagher 546 | Naser 547 | Shadid 548 | Atiyeh 549 | Zogby 550 | Abboud 551 | Tannous 552 | Khouri 553 | Atiyeh 554 | Ganem 555 | Maalouf 556 | Isa 557 | Maroun 558 | Issa 559 | Khouri 560 | Harb 561 | Nader 562 | Awad 563 | Nahas 564 | Said 565 | Baba 566 | Totah 567 | Ganim 568 | Handal 569 | Mansour 570 | Basara 571 | Malouf 572 | Said 573 | Botros 574 | Samaha 575 | Safar 576 | Tahan 577 | Botros 578 | Shamoun 579 | Handal 580 | Sarraf 581 | Malouf 582 | Bishara 583 | Aswad 584 | Khouri 585 | Baz 586 | Asker 587 | Toma 588 | Koury 589 | Gerges 590 | Bishara 591 | Boulos 592 | Najjar 593 | Aswad 594 | Shamon 595 | Kouri 596 | Srour 597 | Assaf 598 | Tannous 599 | Attia 600 | Mustafa 601 | Kattan 602 | Asghar 603 | Amari 604 | Shadid 605 | Said 606 | Bazzi 607 | Masih 608 | Antar 609 | Fakhoury 610 | Shadid 611 | Masih 612 | Handal 613 | Sarraf 614 | Kassis 615 | Salib 616 | Hajjar 617 | Totah 618 | Koury 619 | Totah 620 | Mustafa 621 | Sabbagh 622 | Moghadam 623 | Toma 624 | Srour 625 | Almasi 626 | Totah 627 | Maroun 628 | Kattan 629 | Naifeh 630 | Sarkis 631 | Mikhail 632 | Nazari 633 | Boutros 634 | Guirguis 635 | Gaber 636 | Kassis 637 | Masih 638 | Hanania 639 | Maloof 640 | Quraishi 641 | Cham 642 | Hadad 643 | Tahan 644 | Bitar 645 | Arian 646 | Gaber 647 | Baz 648 | Mansour 649 | Kalb 650 | Sarkis 651 | Attia 652 | Antar 653 | Asfour 654 | Said 655 | Essa 656 | Koury 657 | Hadad 658 | Tuma 659 | Moghadam 660 | Sabbagh 661 | Amari 662 | Dagher 663 | Srour 664 | Antoun 665 | Sleiman 666 | Maroun 667 | Tuma 668 | Nahas 669 | Hanania 670 | Sayegh 671 | Amari 672 | Sabbagh 673 | Said 674 | Cham 675 | Asker 676 | Nassar 677 | Bitar 678 | Said 679 | Dagher 680 | Safar 681 | Khouri 682 | Totah 683 | Khoury 684 | Salib 685 | Basara 686 | Abboud 687 | Baz 688 | Isa 689 | Cham 690 | Amari 691 | Mifsud 692 | Hadad 693 | Rahal 694 | Khoury 695 | Bazzi 696 | Basara 697 | Totah 698 | Ghannam 699 | Koury 700 | Malouf 701 | Zogby 702 | Zogby 703 | Boutros 704 | Nassar 705 | Handal 706 | Hajjar 707 | Maloof 708 | Abadi 709 | Maroun 710 | Mifsud 711 | Kalb 712 | Amari 713 | Hakimi 714 | Boutros 715 | Masih 716 | Kattan 717 | Haddad 718 | Arian 719 | Nazari 720 | Assaf 721 | Attia 722 | Wasem 723 | Gerges 724 | Asker 725 | Tahan 726 | Fakhoury 727 | Shadid 728 | Sarraf 729 | Attia 730 | Naifeh 731 | Aswad 732 | Deeb 733 | Tannous 734 | Totah 735 | Cham 736 | Baba 737 | Najjar 738 | Hajjar 739 | Shamoon 740 | Handal 741 | Awad 742 | Guirguis 743 | Awad 744 | Ganem 745 | Naifeh 746 | Khoury 747 | Hajjar 748 | Moghadam 749 | Mikhail 750 | Ghannam 751 | Guirguis 752 | Tannous 753 | Kanaan 754 | Handal 755 | Khoury 756 | Kalb 757 | Qureshi 758 | Najjar 759 | Atiyeh 760 | Gerges 761 | Nassar 762 | Tahan 763 | Hadad 764 | Fakhoury 765 | Salib 766 | Wasem 767 | Bitar 768 | Fakhoury 769 | Attia 770 | Awad 771 | Totah 772 | Deeb 773 | Touma 774 | Botros 775 | Nazari 776 | Nahas 777 | Kouri 778 | Ghannam 779 | Assaf 780 | Asfour 781 | Sarraf 782 | Naifeh 783 | Toma 784 | Asghar 785 | Abboud 786 | Issa 787 | Sabbag 788 | Sabbagh 789 | Isa 790 | Koury 791 | Kattan 792 | Shamoon 793 | Rahal 794 | Kalb 795 | Naser 796 | Masih 797 | Sayegh 798 | Dagher 799 | Asker 800 | Maroun 801 | Dagher 802 | Sleiman 803 | Botros 804 | Sleiman 805 | Harb 806 | Tahan 807 | Tuma 808 | Said 809 | Hadad 810 | Samaha 811 | Harb 812 | Cham 813 | Atiyeh 814 | Haik 815 | Malouf 816 | Bazzi 817 | Harb 818 | Malouf 819 | Ghanem 820 | Cham 821 | Asghar 822 | Samaha 823 | Khouri 824 | Nassar 825 | Rahal 826 | Baz 827 | Kalb 828 | Rahal 829 | Gerges 830 | Cham 831 | Sayegh 832 | Shadid 833 | Morcos 834 | Shamoon 835 | Hakimi 836 | Shamoon 837 | Qureshi 838 | Ganim 839 | Shadid 840 | Khoury 841 | Boutros 842 | Hanania 843 | Antoun 844 | Naifeh 845 | Deeb 846 | Samaha 847 | Awad 848 | Asghar 849 | Awad 850 | Saliba 851 | Shamoun 852 | Mikhail 853 | Hakimi 854 | Mikhail 855 | Cham 856 | Halabi 857 | Sarkis 858 | Kattan 859 | Nazari 860 | Safar 861 | Morcos 862 | Khoury 863 | Essa 864 | Nassar 865 | Haik 866 | Shadid 867 | Fakhoury 868 | Najjar 869 | Arian 870 | Botros 871 | Daher 872 | Saliba 873 | Saliba 874 | Kattan 875 | Hajjar 876 | Nader 877 | Daher 878 | Nassar 879 | Maroun 880 | Harb 881 | Nassar 882 | Antar 883 | Shammas 884 | Toma 885 | Antar 886 | Koury 887 | Nader 888 | Botros 889 | Bahar 890 | Najjar 891 | Maloof 892 | Salib 893 | Malouf 894 | Mansour 895 | Bazzi 896 | Atiyeh 897 | Kanaan 898 | Bishara 899 | Hakimi 900 | Saliba 901 | Tuma 902 | Mifsud 903 | Hakimi 904 | Assaf 905 | Nassar 906 | Sarkis 907 | Bitar 908 | Isa 909 | Halabi 910 | Shamon 911 | Qureshi 912 | Bishara 913 | Maalouf 914 | Srour 915 | Boulos 916 | Safar 917 | Shamoun 918 | Ganim 919 | Abadi 920 | Koury 921 | Shadid 922 | Zogby 923 | Boutros 924 | Shadid 925 | Hakimi 926 | Bazzi 927 | Isa 928 | Totah 929 | Salib 930 | Shamoon 931 | Gaber 932 | Antar 933 | Antar 934 | Najjar 935 | Fakhoury 936 | Malouf 937 | Salib 938 | Rahal 939 | Boulos 940 | Attia 941 | Said 942 | Kassis 943 | Bahar 944 | Bazzi 945 | Srour 946 | Antar 947 | Nahas 948 | Kassis 949 | Samaha 950 | Quraishi 951 | Asghar 952 | Asker 953 | Antar 954 | Totah 955 | Haddad 956 | Maloof 957 | Kouri 958 | Basara 959 | Bata 960 | Antar 961 | Shammas 962 | Arian 963 | Gerges 964 | Seif 965 | Almasi 966 | Tuma 967 | Shamoon 968 | Khoury 969 | Hakimi 970 | Abboud 971 | Baz 972 | Seif 973 | Issa 974 | Nazari 975 | Harb 976 | Shammas 977 | Amari 978 | Totah 979 | Malouf 980 | Sarkis 981 | Naser 982 | Zogby 983 | Handal 984 | Naifeh 985 | Cham 986 | Hadad 987 | Gerges 988 | Kalb 989 | Shalhoub 990 | Saliba 991 | Tannous 992 | Tahan 993 | Tannous 994 | Kassis 995 | Shadid 996 | Sabbag 997 | Tahan 998 | Abboud 999 | Nahas 1000 | Shamoun 1001 | Dagher 1002 | Botros 1003 | Amari 1004 | Maalouf 1005 | Awad 1006 | Gerges 1007 | Shamoon 1008 | Haddad 1009 | Salib 1010 | Attia 1011 | Kassis 1012 | Sleiman 1013 | Maloof 1014 | Maroun 1015 | Koury 1016 | Asghar 1017 | Kalb 1018 | Asghar 1019 | Touma 1020 | Ganim 1021 | Rahal 1022 | Haddad 1023 | Zogby 1024 | Mansour 1025 | Guirguis 1026 | Touma 1027 | Maroun 1028 | Tannous 1029 | Hakimi 1030 | Baba 1031 | Toma 1032 | Botros 1033 | Sarraf 1034 | Koury 1035 | Sarraf 1036 | Nassar 1037 | Boutros 1038 | Guirguis 1039 | Qureshi 1040 | Aswad 1041 | Basara 1042 | Toma 1043 | Tuma 1044 | Mansour 1045 | Ba 1046 | Naifeh 1047 | Mikhail 1048 | Amari 1049 | Shamon 1050 | Malouf 1051 | Boutros 1052 | Hakimi 1053 | Srour 1054 | Morcos 1055 | Halabi 1056 | Bazzi 1057 | Abadi 1058 | Shamoun 1059 | Haddad 1060 | Baz 1061 | Baba 1062 | Hadad 1063 | Saliba 1064 | Haddad 1065 | Maalouf 1066 | Bitar 1067 | Shammas 1068 | Totah 1069 | Said 1070 | Najjar 1071 | Mikhail 1072 | Samaha 1073 | Boulos 1074 | Kalb 1075 | Shamon 1076 | Shamoun 1077 | Seif 1078 | Touma 1079 | Hajjar 1080 | Hadad 1081 | Atiyeh 1082 | Totah 1083 | Mansour 1084 | Nazari 1085 | Quraishi 1086 | Ba 1087 | Sarkis 1088 | Gerges 1089 | Shalhoub 1090 | Nazari 1091 | Issa 1092 | Salib 1093 | Shalhoub 1094 | Nassar 1095 | Guirguis 1096 | Daher 1097 | Hakimi 1098 | Attia 1099 | Cham 1100 | Isa 1101 | Hakimi 1102 | Amari 1103 | Boutros 1104 | Sarraf 1105 | Antoun 1106 | Botros 1107 | Haddad 1108 | Tahan 1109 | Bishara 1110 | Shalhoub 1111 | Safar 1112 | Haik 1113 | Tahan 1114 | Seif 1115 | Awad 1116 | Antoun 1117 | Atiyeh 1118 | Samaha 1119 | Assaf 1120 | Guirguis 1121 | Hadad 1122 | Sayegh 1123 | Khouri 1124 | Asghar 1125 | Tannous 1126 | Maalouf 1127 | Khouri 1128 | Hajjar 1129 | Abadi 1130 | Ghanem 1131 | Salib 1132 | Botros 1133 | Bitar 1134 | Bishara 1135 | Quraishi 1136 | Boutros 1137 | Aswad 1138 | Srour 1139 | Shamon 1140 | Abboud 1141 | Almasi 1142 | Baba 1143 | Tahan 1144 | Essa 1145 | Sabbag 1146 | Issa 1147 | Abadi 1148 | Abboud 1149 | Bazzi 1150 | Nader 1151 | Bahar 1152 | Ghannam 1153 | Asghar 1154 | Gaber 1155 | Sayegh 1156 | Guirguis 1157 | Srour 1158 | Asghar 1159 | Quraishi 1160 | Sayegh 1161 | Rahal 1162 | Tahan 1163 | Morcos 1164 | Cham 1165 | Kanaan 1166 | Nahas 1167 | Essa 1168 | Mifsud 1169 | Kouri 1170 | Isa 1171 | Saliba 1172 | Asfour 1173 | Guirguis 1174 | Isa 1175 | Bishara 1176 | Assaf 1177 | Naser 1178 | Moghadam 1179 | Kalb 1180 | Baba 1181 | Guirguis 1182 | Naifeh 1183 | Bitar 1184 | Samaha 1185 | Abboud 1186 | Hadad 1187 | Ghannam 1188 | Hanania 1189 | Shadid 1190 | Totah 1191 | Tahan 1192 | Toma 1193 | Maloof 1194 | Botros 1195 | Issa 1196 | Deeb 1197 | Nahas 1198 | Khoury 1199 | Sayegh 1200 | Harb 1201 | Said 1202 | Guirguis 1203 | Nader 1204 | Harb 1205 | Atiyeh 1206 | Zogby 1207 | Basara 1208 | Nassar 1209 | Kalb 1210 | Khoury 1211 | Mifsud 1212 | Wasem 1213 | Handal 1214 | Ganim 1215 | Harb 1216 | Ganim 1217 | Malouf 1218 | Sayegh 1219 | Khoury 1220 | Sabbag 1221 | Sabbag 1222 | Boulos 1223 | Malouf 1224 | Gaber 1225 | Shammas 1226 | Fakhoury 1227 | Halabi 1228 | Haddad 1229 | Asker 1230 | Morcos 1231 | Hanania 1232 | Amari 1233 | Kassab 1234 | Malouf 1235 | Khouri 1236 | Moghadam 1237 | Totah 1238 | Maloof 1239 | Atiyeh 1240 | Abadi 1241 | Baz 1242 | Khoury 1243 | Arian 1244 | Handal 1245 | Dagher 1246 | Awad 1247 | Atiyeh 1248 | Arian 1249 | Khoury 1250 | Amari 1251 | Attia 1252 | Ganim 1253 | Nader 1254 | Dagher 1255 | Sabbag 1256 | Halabi 1257 | Khouri 1258 | Khouri 1259 | Saliba 1260 | Mifsud 1261 | Koury 1262 | Awad 1263 | Bahar 1264 | Mustafa 1265 | Kassis 1266 | Gaber 1267 | Mifsud 1268 | Bishara 1269 | Asker 1270 | Nahas 1271 | Wasem 1272 | Sleiman 1273 | Bata 1274 | Daher 1275 | Antar 1276 | Isa 1277 | Ganim 1278 | Rahal 1279 | Toma 1280 | Rahal 1281 | Shamoun 1282 | Maloof 1283 | Hakimi 1284 | Safar 1285 | Gerges 1286 | Hanania 1287 | Koury 1288 | Assaf 1289 | Safar 1290 | Gerges 1291 | Ganim 1292 | Morcos 1293 | Awad 1294 | Arian 1295 | Tahan 1296 | Sleiman 1297 | Asker 1298 | Boulos 1299 | Koury 1300 | Mifsud 1301 | Sabbag 1302 | Dagher 1303 | Bazzi 1304 | Mustafa 1305 | Almasi 1306 | Handal 1307 | Isa 1308 | Guirguis 1309 | Sayegh 1310 | Ganim 1311 | Ghanem 1312 | Toma 1313 | Mustafa 1314 | Basara 1315 | Bitar 1316 | Samaha 1317 | Mifsud 1318 | Tahan 1319 | Issa 1320 | Salib 1321 | Khoury 1322 | Hadad 1323 | Haik 1324 | Gaber 1325 | Mansour 1326 | Hakimi 1327 | Ba 1328 | Mustafa 1329 | Gaber 1330 | Kattan 1331 | Koury 1332 | Awad 1333 | Maalouf 1334 | Masih 1335 | Harb 1336 | Atiyeh 1337 | Zogby 1338 | Nahas 1339 | Assaf 1340 | Morcos 1341 | Ganem 1342 | Ganem 1343 | Wasem 1344 | Fakhoury 1345 | Ghanem 1346 | Salib 1347 | Khouri 1348 | Maloof 1349 | Khouri 1350 | Shalhoub 1351 | Issa 1352 | Najjar 1353 | Kassis 1354 | Mustafa 1355 | Sayegh 1356 | Kassis 1357 | Hajjar 1358 | Nader 1359 | Sarkis 1360 | Tahan 1361 | Haddad 1362 | Antar 1363 | Sayegh 1364 | Zogby 1365 | Mifsud 1366 | Kassab 1367 | Hanania 1368 | Bishara 1369 | Shamoun 1370 | Abboud 1371 | Mustafa 1372 | Sleiman 1373 | Abadi 1374 | Sarraf 1375 | Zogby 1376 | Daher 1377 | Issa 1378 | Nazari 1379 | Shamon 1380 | Tuma 1381 | Asghar 1382 | Morcos 1383 | Mifsud 1384 | Cham 1385 | Sarraf 1386 | Antar 1387 | Ba 1388 | Aswad 1389 | Mikhail 1390 | Kouri 1391 | Mikhail 1392 | Awad 1393 | Halabi 1394 | Moghadam 1395 | Mikhail 1396 | Naifeh 1397 | Kattan 1398 | Shammas 1399 | Malouf 1400 | Najjar 1401 | Srour 1402 | Masih 1403 | Fakhoury 1404 | Khouri 1405 | Assaf 1406 | Mifsud 1407 | Malouf 1408 | Abboud 1409 | Shamoon 1410 | Mansour 1411 | Halabi 1412 | Ganem 1413 | Deeb 1414 | Wasem 1415 | Kalb 1416 | Safar 1417 | Tuma 1418 | Fakhoury 1419 | Toma 1420 | Guirguis 1421 | Kassab 1422 | Nader 1423 | Handal 1424 | Baba 1425 | Fakhoury 1426 | Haik 1427 | Guirguis 1428 | Seif 1429 | Almasi 1430 | Shamon 1431 | Ba 1432 | Salib 1433 | Zogby 1434 | Koury 1435 | Najjar 1436 | Atiyeh 1437 | Morcos 1438 | Antar 1439 | Awad 1440 | Hadad 1441 | Maroun 1442 | Touma 1443 | Almasi 1444 | Kassis 1445 | Arian 1446 | Malouf 1447 | Koury 1448 | Sarraf 1449 | Hadad 1450 | Bata 1451 | Tuma 1452 | Sarkis 1453 | Quraishi 1454 | Gaber 1455 | Abadi 1456 | Nader 1457 | Bazzi 1458 | Ghannam 1459 | Botros 1460 | Deeb 1461 | Awad 1462 | Kattan 1463 | Kanaan 1464 | Sarraf 1465 | Nahas 1466 | Assaf 1467 | Shadid 1468 | Gaber 1469 | Samaha 1470 | Harb 1471 | Samaha 1472 | Zogby 1473 | Atiyeh 1474 | Mustafa 1475 | Hanania 1476 | Isa 1477 | Almasi 1478 | Bitar 1479 | Fakhoury 1480 | Moghadam 1481 | Handal 1482 | Seif 1483 | Mustafa 1484 | Rahal 1485 | Antoun 1486 | Kassab 1487 | Bazzi 1488 | Hadad 1489 | Nader 1490 | Tuma 1491 | Basara 1492 | Totah 1493 | Nassar 1494 | Seif 1495 | Nassar 1496 | Daher 1497 | Daher 1498 | Maalouf 1499 | Rahal 1500 | Quraishi 1501 | Hadad 1502 | Bahar 1503 | Sabbag 1504 | Halabi 1505 | Tuma 1506 | Antoun 1507 | Boutros 1508 | Gerges 1509 | Bishara 1510 | Baba 1511 | Zogby 1512 | Nahas 1513 | Atiyeh 1514 | Rahal 1515 | Sabbagh 1516 | Bitar 1517 | Botros 1518 | Tuma 1519 | Ganim 1520 | Handal 1521 | Daher 1522 | Boutros 1523 | Khouri 1524 | Maroun 1525 | Mifsud 1526 | Arian 1527 | Safar 1528 | Koury 1529 | Deeb 1530 | Shamoun 1531 | Cham 1532 | Asghar 1533 | Morcos 1534 | Tahan 1535 | Salib 1536 | Aswad 1537 | Shadid 1538 | Saliba 1539 | Ganim 1540 | Haik 1541 | Kattan 1542 | Antoun 1543 | Hajjar 1544 | Toma 1545 | Toma 1546 | Antoun 1547 | Tahan 1548 | Haik 1549 | Kassis 1550 | Shamoun 1551 | Shammas 1552 | Kassis 1553 | Shadid 1554 | Samaha 1555 | Sarraf 1556 | Nader 1557 | Ganem 1558 | Zogby 1559 | Maloof 1560 | Kalb 1561 | Gerges 1562 | Seif 1563 | Nahas 1564 | Arian 1565 | Asfour 1566 | Hakimi 1567 | Ba 1568 | Handal 1569 | Abadi 1570 | Harb 1571 | Nader 1572 | Asghar 1573 | Sabbag 1574 | Touma 1575 | Amari 1576 | Kanaan 1577 | Hajjar 1578 | Said 1579 | Sarraf 1580 | Haddad 1581 | Mifsud 1582 | Shammas 1583 | Sleiman 1584 | Asfour 1585 | Deeb 1586 | Kattan 1587 | Naser 1588 | Said 1589 | Bishara 1590 | Harb 1591 | Morcos 1592 | Sayegh 1593 | Said 1594 | Naser 1595 | Aswad 1596 | Seif 1597 | Kouri 1598 | Dagher 1599 | Shamon 1600 | Hadad 1601 | Handal 1602 | Tuma 1603 | Shamon 1604 | Hakimi 1605 | Rahal 1606 | Hadad 1607 | Ghannam 1608 | Almasi 1609 | Daher 1610 | Handal 1611 | Malouf 1612 | Mansour 1613 | Sabbagh 1614 | Sabbag 1615 | Saliba 1616 | Haddad 1617 | Tahan 1618 | Khoury 1619 | Harb 1620 | Ganim 1621 | Mansour 1622 | Ganem 1623 | Handal 1624 | Handal 1625 | Antar 1626 | Asfour 1627 | Kouri 1628 | Cham 1629 | Masih 1630 | Saliba 1631 | Qureshi 1632 | Daher 1633 | Safar 1634 | Assaf 1635 | Harb 1636 | Abboud 1637 | Haik 1638 | Ghannam 1639 | Maalouf 1640 | Daher 1641 | Najjar 1642 | Mifsud 1643 | Daher 1644 | Amari 1645 | Saliba 1646 | Kanaan 1647 | Guirguis 1648 | Atiyeh 1649 | Sleiman 1650 | Mikhail 1651 | Arian 1652 | Wasem 1653 | Attia 1654 | Nassar 1655 | Cham 1656 | Koury 1657 | Baba 1658 | Guirguis 1659 | Morcos 1660 | Quraishi 1661 | Seif 1662 | Sarkis 1663 | Moghadam 1664 | Ba 1665 | Boutros 1666 | Nader 1667 | Gerges 1668 | Salib 1669 | Salib 1670 | Guirguis 1671 | Essa 1672 | Guirguis 1673 | Antoun 1674 | Kassis 1675 | Abboud 1676 | Najjar 1677 | Aswad 1678 | Srour 1679 | Mifsud 1680 | Ghanem 1681 | Bitar 1682 | Ghannam 1683 | Asghar 1684 | Deeb 1685 | Kalb 1686 | Nader 1687 | Srour 1688 | Attia 1689 | Shamon 1690 | Bata 1691 | Nahas 1692 | Gerges 1693 | Kanaan 1694 | Kassis 1695 | Sarkis 1696 | Maloof 1697 | Almasi 1698 | Nassar 1699 | Saliba 1700 | Arian 1701 | Ghanem 1702 | Awad 1703 | Naifeh 1704 | Boutros 1705 | Fakhoury 1706 | Sabbag 1707 | Antar 1708 | Tahan 1709 | Mustafa 1710 | Almasi 1711 | Shammas 1712 | Totah 1713 | Boutros 1714 | Cham 1715 | Shamon 1716 | Ganim 1717 | Ghanem 1718 | Assaf 1719 | Khoury 1720 | Naifeh 1721 | Bahar 1722 | Quraishi 1723 | Bishara 1724 | Cham 1725 | Asfour 1726 | Ghannam 1727 | Khoury 1728 | Sayegh 1729 | Hanania 1730 | Maroun 1731 | Kouri 1732 | Sarkis 1733 | Haik 1734 | Basara 1735 | Salib 1736 | Shammas 1737 | Fakhoury 1738 | Nahas 1739 | Ganim 1740 | Botros 1741 | Arian 1742 | Shalhoub 1743 | Hadad 1744 | Mustafa 1745 | Shalhoub 1746 | Kassab 1747 | Asker 1748 | Botros 1749 | Kanaan 1750 | Gaber 1751 | Bazzi 1752 | Sayegh 1753 | Nassar 1754 | Kassis 1755 | Fakhoury 1756 | Kassis 1757 | Amari 1758 | Sarraf 1759 | Mifsud 1760 | Salib 1761 | Samaha 1762 | Mustafa 1763 | Asfour 1764 | Najjar 1765 | Essa 1766 | Naifeh 1767 | Cham 1768 | Sarraf 1769 | Moghadam 1770 | Fakhoury 1771 | Assaf 1772 | Almasi 1773 | Asghar 1774 | Nader 1775 | Kalb 1776 | Shamoun 1777 | Gerges 1778 | Wasem 1779 | Morcos 1780 | Nader 1781 | Said 1782 | Safar 1783 | Quraishi 1784 | Samaha 1785 | Kassab 1786 | Deeb 1787 | Sarraf 1788 | Rahal 1789 | Naifeh 1790 | Ba 1791 | Nazari 1792 | Ganim 1793 | Arian 1794 | Asker 1795 | Touma 1796 | Kassab 1797 | Tahan 1798 | Mansour 1799 | Morcos 1800 | Shammas 1801 | Baba 1802 | Morcos 1803 | Isa 1804 | Moghadam 1805 | Ganem 1806 | Baz 1807 | Totah 1808 | Nader 1809 | Kouri 1810 | Guirguis 1811 | Koury 1812 | Zogby 1813 | Basara 1814 | Baz 1815 | Deeb 1816 | Mustafa 1817 | Shadid 1818 | Awad 1819 | Sarraf 1820 | Quraishi 1821 | Kanaan 1822 | Tahan 1823 | Ghannam 1824 | Shammas 1825 | Abboud 1826 | Najjar 1827 | Bishara 1828 | Tuma 1829 | Srour 1830 | Mifsud 1831 | Srour 1832 | Hajjar 1833 | Qureshi 1834 | Bitar 1835 | Hadad 1836 | Almasi 1837 | Wasem 1838 | Abadi 1839 | Maroun 1840 | Baz 1841 | Koury 1842 | Ganem 1843 | Awad 1844 | Maalouf 1845 | Mifsud 1846 | Haik 1847 | Sleiman 1848 | Arian 1849 | Seif 1850 | Mansour 1851 | Koury 1852 | Kattan 1853 | Koury 1854 | Aswad 1855 | Ba 1856 | Rahal 1857 | Zogby 1858 | Bahar 1859 | Fakhoury 1860 | Samaha 1861 | Sarraf 1862 | Mifsud 1863 | Antar 1864 | Moghadam 1865 | Botros 1866 | Srour 1867 | Sabbag 1868 | Sayegh 1869 | Rahal 1870 | Attia 1871 | Naifeh 1872 | Saliba 1873 | Mustafa 1874 | Amari 1875 | Issa 1876 | Masih 1877 | Khouri 1878 | Haddad 1879 | Kalb 1880 | Bazzi 1881 | Salib 1882 | Hanania 1883 | Shamoon 1884 | Tuma 1885 | Cham 1886 | Antoun 1887 | Wasem 1888 | Kouri 1889 | Ghanem 1890 | Wasem 1891 | Khoury 1892 | Assaf 1893 | Ganem 1894 | Seif 1895 | Nader 1896 | Essa 1897 | Shadid 1898 | Botros 1899 | Sleiman 1900 | Bishara 1901 | Basara 1902 | Maalouf 1903 | Issa 1904 | Nassar 1905 | Moghadam 1906 | Ganim 1907 | Kassis 1908 | Antoun 1909 | Said 1910 | Khouri 1911 | Salib 1912 | Baz 1913 | Sarkis 1914 | Tuma 1915 | Naifeh 1916 | Najjar 1917 | Asker 1918 | Khouri 1919 | Mustafa 1920 | Najjar 1921 | Sabbag 1922 | Malouf 1923 | Wasem 1924 | Maalouf 1925 | Gaber 1926 | Said 1927 | Zogby 1928 | Bahar 1929 | Hanania 1930 | Shalhoub 1931 | Abadi 1932 | Handal 1933 | Qureshi 1934 | Kanaan 1935 | Abboud 1936 | Mifsud 1937 | Touma 1938 | Ganim 1939 | Bishara 1940 | Bazzi 1941 | Gaber 1942 | Haik 1943 | Ghanem 1944 | Sarraf 1945 | Sarkis 1946 | Mustafa 1947 | Baz 1948 | Kanaan 1949 | Nazari 1950 | Bahar 1951 | Malouf 1952 | Quraishi 1953 | Kattan 1954 | Arian 1955 | Shadid 1956 | Tuma 1957 | Nader 1958 | Khoury 1959 | Safar 1960 | Wasem 1961 | Toma 1962 | Haddad 1963 | Quraishi 1964 | Nassar 1965 | Kanaan 1966 | Gaber 1967 | Haddad 1968 | Rahal 1969 | Koury 1970 | Harb 1971 | Mikhail 1972 | Dagher 1973 | Shadid 1974 | Boutros 1975 | Mikhail 1976 | Khouri 1977 | Nader 1978 | Issa 1979 | Harb 1980 | Dagher 1981 | Gerges 1982 | Morcos 1983 | Essa 1984 | Fakhoury 1985 | Tuma 1986 | Kattan 1987 | Totah 1988 | Qureshi 1989 | Nahas 1990 | Bitar 1991 | Tahan 1992 | Daher 1993 | Shammas 1994 | Kouri 1995 | Ganim 1996 | Daher 1997 | Awad 1998 | Malouf 1999 | Mustafa 2000 | Aswad 2001 | -------------------------------------------------------------------------------- /data/names/Chinese.txt: -------------------------------------------------------------------------------- 1 | Ang 2 | Au-Yong 3 | Bai 4 | Ban 5 | Bao 6 | Bei 7 | Bian 8 | Bui 9 | Cai 10 | Cao 11 | Cen 12 | Chai 13 | Chaim 14 | Chan 15 | Chang 16 | Chao 17 | Che 18 | Chen 19 | Cheng 20 | Cheung 21 | Chew 22 | Chieu 23 | Chin 24 | Chong 25 | Chou 26 | Chu 27 | Cui 28 | Dai 29 | Deng 30 | Ding 31 | Dong 32 | Dou 33 | Duan 34 | Eng 35 | Fan 36 | Fei 37 | Feng 38 | Foong 39 | Fung 40 | Gan 41 | Gauk 42 | Geng 43 | Gim 44 | Gok 45 | Gong 46 | Guan 47 | Guang 48 | Guo 49 | Gwock 50 | Han 51 | Hang 52 | Hao 53 | Hew 54 | Hiu 55 | Hong 56 | Hor 57 | Hsiao 58 | Hua 59 | Huan 60 | Huang 61 | Hui 62 | Huie 63 | Huo 64 | Jia 65 | Jiang 66 | Jin 67 | Jing 68 | Joe 69 | Kang 70 | Kau 71 | Khoo 72 | Khu 73 | Kong 74 | Koo 75 | Kwan 76 | Kwei 77 | Kwong 78 | Lai 79 | Lam 80 | Lang 81 | Lau 82 | Law 83 | Lew 84 | Lian 85 | Liao 86 | Lim 87 | Lin 88 | Ling 89 | Liu 90 | Loh 91 | Long 92 | Loong 93 | Luo 94 | Mah 95 | Mai 96 | Mak 97 | Mao 98 | Mar 99 | Mei 100 | Meng 101 | Miao 102 | Min 103 | Ming 104 | Moy 105 | Mui 106 | Nie 107 | Niu 108 | Ou-Yang 109 | Ow-Yang 110 | Pan 111 | Pang 112 | Pei 113 | Peng 114 | Ping 115 | Qian 116 | Qin 117 | Qiu 118 | Quan 119 | Que 120 | Ran 121 | Rao 122 | Rong 123 | Ruan 124 | Sam 125 | Seah 126 | See 127 | Seow 128 | Seto 129 | Sha 130 | Shan 131 | Shang 132 | Shao 133 | Shaw 134 | She 135 | Shen 136 | Sheng 137 | Shi 138 | Shu 139 | Shuai 140 | Shui 141 | Shum 142 | Siew 143 | Siu 144 | Song 145 | Sum 146 | Sun 147 | Sze 148 | Tan 149 | Tang 150 | Tao 151 | Teng 152 | Teoh 153 | Thean 154 | Thian 155 | Thien 156 | Tian 157 | Tong 158 | Tow 159 | Tsang 160 | Tse 161 | Tsen 162 | Tso 163 | Tze 164 | Wan 165 | Wang 166 | Wei 167 | Wen 168 | Weng 169 | Won 170 | Wong 171 | Woo 172 | Xiang 173 | Xiao 174 | Xie 175 | Xing 176 | Xue 177 | Xun 178 | Yan 179 | Yang 180 | Yao 181 | Yap 182 | Yau 183 | Yee 184 | Yep 185 | Yim 186 | Yin 187 | Ying 188 | Yong 189 | You 190 | Yuan 191 | Zang 192 | Zeng 193 | Zha 194 | Zhan 195 | Zhang 196 | Zhao 197 | Zhen 198 | Zheng 199 | Zhong 200 | Zhou 201 | Zhu 202 | Zhuo 203 | Zong 204 | Zou 205 | Bing 206 | Chi 207 | Chu 208 | Cong 209 | Cuan 210 | Dan 211 | Fei 212 | Feng 213 | Gai 214 | Gao 215 | Gou 216 | Guan 217 | Gui 218 | Guo 219 | Hong 220 | Hou 221 | Huan 222 | Jian 223 | Jiao 224 | Jin 225 | Jiu 226 | Juan 227 | Jue 228 | Kan 229 | Kuai 230 | Kuang 231 | Kui 232 | Lao 233 | Liang 234 | Lu: 235 | Luo 236 | Man 237 | Nao 238 | Pian 239 | Qiao 240 | Qing 241 | Qiu 242 | Rang 243 | Rui 244 | She 245 | Shi 246 | Shuo 247 | Sui 248 | Tai 249 | Wan 250 | Wei 251 | Xian 252 | Xie 253 | Xin 254 | Xing 255 | Xiong 256 | Xuan 257 | Yan 258 | Yin 259 | Ying 260 | Yuan 261 | Yue 262 | Yun 263 | Zha 264 | Zhai 265 | Zhang 266 | Zhi 267 | Zhuan 268 | Zhui 269 | -------------------------------------------------------------------------------- /data/names/Czech.txt: -------------------------------------------------------------------------------- 1 | Abl 2 | Adsit 3 | Ajdrna 4 | Alt 5 | Antonowitsch 6 | Antonowitz 7 | Bacon 8 | Ballalatak 9 | Ballaltick 10 | Bartonova 11 | Bastl 12 | Baroch 13 | Benesch 14 | Betlach 15 | Biganska 16 | Bilek 17 | Blahut 18 | Blazek 19 | Blazek 20 | Blazejovsky 21 | Blecha 22 | Bleskan 23 | Blober 24 | Bock 25 | Bohac 26 | Bohunovsky 27 | Bolcar 28 | Borovka 29 | Borovski 30 | Borowski 31 | Borovsky 32 | Brabbery 33 | Brezovjak 34 | Brousil 35 | Bruckner 36 | Buchta 37 | Cablikova 38 | Camfrlova 39 | Cap 40 | Cerda 41 | Cermak 42 | Chermak 43 | Cermak 44 | Cernochova 45 | Cernohous 46 | Cerny 47 | Cerney 48 | Cerny 49 | Cerv 50 | Cervenka 51 | Chalupka 52 | Charlott 53 | Chemlik 54 | Chicken 55 | Chilar 56 | Chromy 57 | Cihak 58 | Clineburg 59 | Klineberg 60 | Cober 61 | Colling 62 | Cvacek 63 | Czabal 64 | Damell 65 | Demall 66 | Dehmel 67 | Dana 68 | Dejmal 69 | Dempko 70 | Demko 71 | Dinko 72 | Divoky 73 | Dolejsi 74 | Dolezal 75 | Doljs 76 | Dopita 77 | Drassal 78 | Driml 79 | Duyava 80 | Dvorak 81 | Dziadik 82 | Egr 83 | Entler 84 | Faltysek 85 | Faltejsek 86 | Fencl 87 | Fenyo 88 | Fillipova 89 | Finfera 90 | Finferovy 91 | Finke 92 | Fojtikova 93 | Fremut 94 | Friedrich 95 | Frierdich 96 | Fritsch 97 | Furtsch 98 | Gabrisova 99 | Gavalok 100 | Geier 101 | Georgijev 102 | Geryk 103 | Giersig 104 | Glatter 105 | Glockl 106 | Grabski 107 | Grozmanova 108 | Grulich 109 | Grygarova 110 | Hadash 111 | Hafernik 112 | Hajek 113 | Hajicek 114 | Hajkova 115 | Hana 116 | Hanek 117 | Hanek 118 | Hanika 119 | Hanusch 120 | Hanzlick 121 | Handzlik 122 | Hanzlik 123 | Harger 124 | Hartl 125 | Havlatova 126 | Havlice 127 | Hawlata 128 | Heidl 129 | Herback 130 | Herodes 131 | Hiorvst 132 | Hladky 133 | Hlavsa 134 | Hnizdil 135 | Hodowal 136 | Hodoval 137 | Holan 138 | Holub 139 | Homulka 140 | Hora 141 | Hovanec 142 | Hrabak 143 | Hradek 144 | Hrdy 145 | Hrula 146 | Hruska 147 | Hruskova 148 | Hudecek 149 | Husk 150 | Hynna 151 | Jaluvka 152 | Janca 153 | Janicek 154 | Jenicek 155 | Janacek 156 | Janick 157 | Janoch 158 | Janosik 159 | Janutka 160 | Jares 161 | Jarzembowski 162 | Jedlicka 163 | Jelinek 164 | Jindra 165 | Jirava 166 | Jirik 167 | Jirku 168 | Jirovy 169 | Jobst 170 | Jonas 171 | Kacirek 172 | Kafka 173 | Kafka 174 | Kaiser 175 | Kanak 176 | Kaplanek 177 | Kara 178 | Karlovsky 179 | Kasa 180 | Kasimor 181 | Kazimor 182 | Kazmier 183 | Katschker 184 | Kauphsman 185 | Kenzel 186 | Kerner 187 | Kesl 188 | Kessel 189 | Kessler 190 | Khork 191 | Kirchma 192 | Klein 193 | Klemper 194 | Klimes 195 | Kober 196 | Koberna 197 | Koci 198 | Kocian 199 | Kocian 200 | Kofron 201 | Kolacny 202 | Koliha 203 | Kolman 204 | Koma 205 | Komo 206 | Coma 207 | Konarik 208 | Kopp 209 | Kopecky 210 | Korandak 211 | Korycan 212 | Korycansky 213 | Kosko 214 | Kouba 215 | Kouba 216 | Koukal 217 | Koza 218 | Kozumplikova 219 | Kratschmar 220 | Krawiec 221 | Kreisinger 222 | Kremlacek 223 | Kremlicka 224 | Kreutschmer 225 | Krhovsky 226 | Krivan 227 | Krivolavy 228 | Kriz 229 | Kruessel 230 | Krupala 231 | Krytinar 232 | Kubin 233 | Kucera 234 | Kucharova 235 | Kudrna 236 | Kuffel 237 | Kupfel 238 | Kofel 239 | Kulhanek 240 | Kunik 241 | Kurtz 242 | Kusak 243 | Kvasnicka 244 | Lawa 245 | Linart 246 | Lind 247 | Lokay 248 | Loskot 249 | Ludwig 250 | Lynsmeier 251 | Macha 252 | Machacek 253 | Macikova 254 | Malafa 255 | Malec 256 | Malecha 257 | Maly 258 | Marek 259 | Marik 260 | Marik 261 | Markytan 262 | Matejka 263 | Matjeka 264 | Matocha 265 | Maxa/B 266 | Mayer 267 | Meier 268 | Merta 269 | Meszes 270 | Metjeka 271 | Michalovic 272 | Michalovicova 273 | Miksatkova 274 | Mojzis 275 | Mojjis 276 | Mozzis 277 | Molcan 278 | Monfort 279 | MonkoAustria 280 | Morava 281 | Morek 282 | Muchalon 283 | Mudra 284 | Muhlbauer 285 | Nadvornizch 286 | Nadwornik 287 | Navara 288 | Navratil 289 | Navratil 290 | Navrkal 291 | Nekuza 292 | Nemec 293 | Nemecek 294 | Nestrojil 295 | Netsch 296 | Neusser 297 | Neisser 298 | Naizer 299 | Novak 300 | Nowak 301 | Novotny 302 | Novy Novy 303 | Oborny 304 | Ocasek 305 | Ocaskova 306 | Oesterreicher 307 | Okenfuss 308 | Olbrich 309 | Ondrisek 310 | Opizka 311 | Opova 312 | Opp 313 | Osladil 314 | Ozimuk 315 | Pachr 316 | Palzewicz 317 | Panek 318 | Patril 319 | Pavlik 320 | Pavlicka 321 | Pavlu 322 | Pawlak 323 | Pear 324 | Peary 325 | Pech 326 | Peisar 327 | Paisar 328 | Paiser 329 | Perevuznik 330 | Perina 331 | Persein 332 | Petrezelka 333 | Petru 334 | Pesek 335 | Petersen 336 | Pfeifer 337 | Picha 338 | Pillar 339 | Pellar 340 | Piller 341 | Pinter 342 | Pitterman 343 | Planick 344 | Piskach 345 | Plisek 346 | Plisko 347 | Pokorny 348 | Ponec 349 | Ponec 350 | Prachar 351 | Praseta 352 | Prchal 353 | Prehatney 354 | Pretsch 355 | Prill 356 | Psik 357 | Pudel 358 | Purdes 359 | Quasninsky 360 | Raffel 361 | Rafaj1 362 | Ransom 363 | Rezac 364 | Riedel 365 | Riha 366 | Riha 367 | Ritchie 368 | Rozinek 369 | Ruba 370 | Ruda 371 | Rumisek 372 | Ruzicka 373 | Rypka 374 | Rebka 375 | Rzehak 376 | Sabol 377 | Safko 378 | Samz 379 | Sankovsky 380 | Sappe 381 | Sappe 382 | Sarna 383 | Satorie 384 | Savchak 385 | Svotak 386 | Swatchak 387 | Svocak 388 | Svotchak 389 | Schallom 390 | Schenk 391 | Schlantz 392 | Schmeiser 393 | Schneider 394 | Schmied 395 | Schubert 396 | Schwarz 397 | Schwartz 398 | Sedmik 399 | Sedmikova 400 | Seger 401 | Sekovora 402 | Semick 403 | Serak 404 | Sherak 405 | Shima 406 | Shula 407 | Siegl 408 | Silhan 409 | Simecek 410 | Simodines 411 | Simonek 412 | Sip 413 | Sitta 414 | Skala 415 | Skeril 416 | Skokan 417 | Skomicka 418 | Skwor 419 | Slapnickova 420 | Slejtr 421 | Slepicka 422 | Slepica 423 | Slezak 424 | Slivka 425 | Smith 426 | Snelker 427 | Sokolik 428 | Soucek 429 | Soukup 430 | Soukup 431 | Spicka 432 | Spoerl 433 | Sponer 434 | Srda 435 | Srpcikova 436 | Stangl 437 | Stanzel 438 | Stary 439 | Staska 440 | Stedronsky 441 | Stegon 442 | Sztegon 443 | Steinborn 444 | Stepan 445 | Stites 446 | Stluka 447 | Stotzky 448 | StrakaO 449 | Stramba 450 | Stupka 451 | Subertova 452 | Suchanka 453 | Sula 454 | Svejda 455 | Svejkovsky 456 | Svoboda 457 | Tejc 458 | Tikal 459 | Tykal 460 | Till 461 | Timpe 462 | Timpy 463 | Toman 464 | Tomanek 465 | Tomasek 466 | Tomes 467 | Trampotova 468 | Trampota 469 | Treblik 470 | Trnkova 471 | Uerling 472 | Uhlik 473 | Urbanek 474 | Urbanek1 475 | Urbanovska 476 | Urista 477 | Ustohal 478 | Vaca 479 | Vaculova 480 | Vavra 481 | Vejvoda 482 | Veverka 483 | Victor 484 | Vlach 485 | Vlach 486 | Vlasak 487 | Vlasek 488 | Volcik 489 | Voneve 490 | Votke 491 | Vozab 492 | Vrazel 493 | Vykruta 494 | Wykruta 495 | Waclauska 496 | Weichert 497 | Weineltk 498 | Weisener 499 | Wiesner 500 | Wizner 501 | Weiss 502 | Werlla 503 | Whitmire1 504 | Widerlechner 505 | Wilchek 506 | Wondracek 507 | Wood 508 | Zajicek 509 | Zak 510 | Zajicek 511 | Zaruba 512 | Zaruba 513 | Zelinka 514 | Zeman 515 | Zimola 516 | Zipperer 517 | Zitka 518 | Zoucha 519 | Zwolenksy 520 | -------------------------------------------------------------------------------- /data/names/Dutch.txt: -------------------------------------------------------------------------------- 1 | Aalsburg 2 | Aalst 3 | Aarle 4 | Achteren 5 | Achthoven 6 | Adrichem 7 | Aggelen 8 | Agteren 9 | Agthoven 10 | Akkeren 11 | Aller 12 | Alphen 13 | Alst 14 | Altena 15 | Althuis 16 | Amelsvoort 17 | Amersvoort 18 | Amstel 19 | Andel 20 | Andringa 21 | Ankeren 22 | Antwerp 23 | Antwerpen 24 | Apeldoorn 25 | Arendonk 26 | Asch 27 | Assen 28 | Baarle 29 | Bokhoven 30 | Breda 31 | Bueren 32 | Buggenum 33 | Buiren 34 | Buren 35 | Can 36 | Cann 37 | Canne 38 | Daal 39 | Daalen 40 | Dael 41 | Daele 42 | Dale 43 | Dalen 44 | Laar 45 | Vliert 46 | Akker 47 | Andel 48 | Denend 49 | Aart 50 | Beek 51 | Berg 52 | Hout 53 | Laar 54 | See 55 | Stoep 56 | Veen 57 | Ven 58 | Venn 59 | Venne 60 | Vennen 61 | Zee 62 | Donk 63 | Haanraads 64 | Haanraats 65 | Haanrade 66 | Haanrath 67 | Haenraats 68 | Haenraets 69 | Hanraets 70 | Hassel 71 | Hautem 72 | Hautum 73 | Heel 74 | Herten 75 | Hofwegen 76 | Horn 77 | Hout 78 | Houte 79 | Houtem 80 | Houten 81 | Houttum 82 | Houtum 83 | Kan 84 | Kann 85 | Kanne 86 | Kappel 87 | Karl 88 | Kikkert 89 | Klein 90 | Klerk 91 | Klerken 92 | Klerks 93 | Klerkse 94 | Klerkx 95 | Klerx 96 | Kloet 97 | Kloeten 98 | Kloeter 99 | Koeman 100 | Koemans 101 | Kolen 102 | Kolijn 103 | Kollen 104 | Koning 105 | Kool 106 | Koole 107 | Koolen 108 | Kools 109 | Kouman 110 | Koumans 111 | Krantz 112 | Kranz 113 | Krusen 114 | Kuijpers 115 | Kuiper 116 | Kuipers 117 | Laar 118 | Langbroek 119 | Laren 120 | Lauwens 121 | Lauwers 122 | Leeuwenhoeck 123 | Leeuwenhoek 124 | Leeuwenhoek 125 | Lucas 126 | Lucassen 127 | Lyon 128 | Maas 129 | Maes 130 | Maessen 131 | Marquering 132 | Marqueringh 133 | Marquerink 134 | Mas 135 | Meeuwe 136 | Meeuwes 137 | Meeuwessen 138 | Meeuweszen 139 | Meeuwis 140 | Meeuwissen 141 | Meeuwsen 142 | Meisner 143 | Merckx 144 | Mertens 145 | Michel 146 | Middelburg 147 | Middlesworth 148 | Mohren 149 | Mooren 150 | Mulder 151 | Muyskens 152 | Nagel 153 | Nelissen 154 | Nifterick 155 | Nifterick 156 | Nifterik 157 | Nifterik 158 | Niftrik 159 | Niftrik 160 | Offermans 161 | Ogterop 162 | Ogtrop 163 | Oirschot 164 | Oirschotten 165 | Oomen 166 | Oorschot 167 | Oorschot 168 | Ophoven 169 | Otten 170 | Pander 171 | Panders 172 | Paulis 173 | Paulissen 174 | Peerenboom 175 | Peeters 176 | Peij 177 | Pender 178 | Penders 179 | Pennders 180 | Penner 181 | Penners 182 | Peter 183 | Peusen 184 | Pey 185 | Philips 186 | Prinsen 187 | Rademaker 188 | Rademakers 189 | Ramaaker 190 | Ramaker 191 | Ramakers 192 | Ramecker 193 | Rameckers 194 | Raske 195 | Reijnder 196 | Reijnders 197 | Reinder 198 | Reinders 199 | Reynder 200 | Reynders 201 | Richard 202 | Rietveld 203 | Rijnder 204 | Rijnders 205 | Robert 206 | Roggeveen 207 | Roijacker 208 | Roijackers 209 | Roijakker 210 | Roijakkers 211 | Romeijn 212 | Romeijnders 213 | Romeijnsen 214 | Romijn 215 | Romijnders 216 | Romijnsen 217 | Rompa 218 | Rompa 219 | Rompaeij 220 | Rompaey 221 | Rompaij 222 | Rompay 223 | Rompaye 224 | Rompu 225 | Rompuy 226 | Rooiakker 227 | Rooiakkers 228 | Rooijakker 229 | Rooijakkers 230 | Roosa 231 | Roosevelt 232 | Rossem 233 | Rossum 234 | Rumpade 235 | Rutten 236 | Ryskamp 237 | Samson 238 | Sanna 239 | Schenck 240 | Schermer 241 | Schneider 242 | Schneiders 243 | Schneijder 244 | Schneijders 245 | Schoonenburg 246 | Schoonraad 247 | Schoorel 248 | Schoorel 249 | Schoorl 250 | Schorel 251 | Schrijnemakers 252 | Schuyler 253 | Schwarzenberg 254 | Seeger 255 | Seegers 256 | Seelen 257 | Segers 258 | Segher 259 | Seghers 260 | Severijns 261 | Severins 262 | Sevriens 263 | Silje 264 | Simon 265 | Simonis 266 | Slootmaekers 267 | Smeets 268 | Smets 269 | Smit 270 | Smits 271 | Snaaijer 272 | Snaijer 273 | Sneiders 274 | Sneijder 275 | Sneijders 276 | Sneijer 277 | Sneijers 278 | Snell 279 | Snider 280 | Sniders 281 | Snijder 282 | Snijders 283 | Snyder 284 | Snyders 285 | Specht 286 | Spijker 287 | Spiker 288 | Ter Avest 289 | Teunissen 290 | Theunissen 291 | Tholberg 292 | Tillens 293 | Tunison 294 | Tunneson 295 | Vandale 296 | Vandroogenbroeck 297 | Vann 298 | -------------------------------------------------------------------------------- /data/names/English.txt: -------------------------------------------------------------------------------- 1 | Abbas 2 | Abbey 3 | Abbott 4 | Abdi 5 | Abel 6 | Abraham 7 | Abrahams 8 | Abrams 9 | Ackary 10 | Ackroyd 11 | Acton 12 | Adair 13 | Adam 14 | Adams 15 | Adamson 16 | Adanet 17 | Addams 18 | Adderley 19 | Addinall 20 | Addis 21 | Addison 22 | Addley 23 | Aderson 24 | Adey 25 | Adkins 26 | Adlam 27 | Adler 28 | Adrol 29 | Adsett 30 | Agar 31 | Ahern 32 | Aherne 33 | Ahmad 34 | Ahmed 35 | Aikman 36 | Ainley 37 | Ainsworth 38 | Aird 39 | Airey 40 | Aitchison 41 | Aitken 42 | Akhtar 43 | Akram 44 | Alam 45 | Alanson 46 | Alber 47 | Albert 48 | Albrighton 49 | Albutt 50 | Alcock 51 | Alden 52 | Alder 53 | Aldersley 54 | Alderson 55 | Aldred 56 | Aldren 57 | Aldridge 58 | Aldworth 59 | Alesbury 60 | Alexandar 61 | Alexander 62 | Alexnader 63 | Alford 64 | Algar 65 | Ali 66 | Alker 67 | Alladee 68 | Allam 69 | Allan 70 | Allard 71 | Allaway 72 | Allcock 73 | Allcott 74 | Alldridge 75 | Alldritt 76 | Allen 77 | Allgood 78 | Allington 79 | Alliott 80 | Allison 81 | Allkins 82 | Allman 83 | Allport 84 | Allsop 85 | Allum 86 | Allwood 87 | Almond 88 | Alpin 89 | Alsop 90 | Altham 91 | Althoff 92 | Alves 93 | Alvey 94 | Alway 95 | Ambrose 96 | Amesbury 97 | Amin 98 | Amner 99 | Amod 100 | Amor 101 | Amos 102 | Anakin 103 | Anderson 104 | Andersson 105 | Anderton 106 | Andrew 107 | Andrews 108 | Angus 109 | Anker 110 | Anley 111 | Annan 112 | Anscombe 113 | Ansell 114 | Anstee 115 | Anthony 116 | Antic 117 | Anton 118 | Antony 119 | Antram 120 | Anwar 121 | Appleby 122 | Appleton 123 | Appleyard 124 | Apsley 125 | Arah 126 | Archer 127 | Ardern 128 | Arkins 129 | Armer 130 | Armitage 131 | Armour 132 | Armsden 133 | Armstrong 134 | Arnall 135 | Arnett 136 | Arnold 137 | Arnott 138 | Arrowsmith 139 | Arscott 140 | Arthur 141 | Artliff 142 | Ashbridge 143 | Ashbrook 144 | Ashby 145 | Ashcroft 146 | Ashdown 147 | Ashe 148 | Asher 149 | Ashford 150 | Ashley 151 | Ashman 152 | Ashton 153 | Ashurst 154 | Ashwell 155 | Ashworth 156 | Askew 157 | Aslam 158 | Asom 159 | Aspey 160 | Aspin 161 | Aspinall 162 | Astbury 163 | Astle 164 | Astley 165 | Aston 166 | Atherley 167 | Atherstone 168 | Atherton 169 | Atkin 170 | Atkins 171 | Atkinson 172 | Attard 173 | Atter 174 | Atterbury 175 | Atterton 176 | Attewell 177 | Attrill 178 | Attwood 179 | Auberton 180 | Auborn 181 | Aubrey 182 | Austen 183 | Austin 184 | Auton 185 | Avenue 186 | Avery 187 | Aves 188 | Avis 189 | Awad 190 | Axon 191 | Aylett 192 | Ayley 193 | Ayliffe 194 | Ayling 195 | Aylott 196 | Aylward 197 | Ayres 198 | Ayton 199 | Aziz 200 | Bacon 201 | Bailey 202 | Bain 203 | Bainbridge 204 | Baines 205 | Bains 206 | Baird 207 | Baker 208 | Baldwin 209 | Bale 210 | Ball 211 | Ballantyne 212 | Ballard 213 | Bamford 214 | Bancroft 215 | Banks 216 | Banner 217 | Bannister 218 | Barber 219 | Barclay 220 | Barker 221 | Barlow 222 | Barnard 223 | Barnes 224 | Barnett 225 | Baron 226 | Barr 227 | Barrett 228 | Barron 229 | Barrow 230 | Barry 231 | Bartlett 232 | Barton 233 | Bass 234 | Bassett 235 | Batchelor 236 | Bate 237 | Bateman 238 | Bates 239 | Batt 240 | Batten 241 | Batty 242 | Baxter 243 | Bayliss 244 | Beadle 245 | Beal 246 | Beale 247 | Beamish 248 | Bean 249 | Bear 250 | Beattie 251 | Beatty 252 | Beaumont 253 | Beck 254 | Bedford 255 | Beech 256 | Beer 257 | Begum 258 | Bell 259 | Bellamy 260 | Benfield 261 | Benjamin 262 | Bennett 263 | Benson 264 | Bentley 265 | Berger 266 | Bernard 267 | Berry 268 | Best 269 | Bethell 270 | Betts 271 | Bevan 272 | Beveridge 273 | Bickley 274 | Biddle 275 | Biggs 276 | Bill 277 | Bing 278 | Bingham 279 | Binnington 280 | Birch 281 | Bird 282 | Bishop 283 | Bithell 284 | Black 285 | Blackburn 286 | Blackman 287 | Blackmore 288 | Blackwell 289 | Blair 290 | Blake 291 | Blakeley 292 | Blakey 293 | Blanchard 294 | Bland 295 | Bloggs 296 | Bloom 297 | Blundell 298 | Blythe 299 | Bob 300 | Boden 301 | Boland 302 | Bolton 303 | Bond 304 | Bone 305 | Bonner 306 | Boon 307 | Booth 308 | Borland 309 | Bostock 310 | Boulton 311 | Bourne 312 | Bouvet 313 | Bowden 314 | Bowen 315 | Bower 316 | Bowers 317 | Bowes 318 | Bowler 319 | Bowles 320 | Bowman 321 | Boyce 322 | Boyd 323 | Boyle 324 | Bracey 325 | Bradbury 326 | Bradley 327 | Bradshaw 328 | Brady 329 | Brain 330 | Braithwaite 331 | Bramley 332 | Brandrick 333 | Bray 334 | Breen 335 | Brelsford 336 | Brennan 337 | Brett 338 | Brewer 339 | Bridges 340 | Briggs 341 | Bright 342 | Bristow 343 | Britton 344 | Broadbent 345 | Broadhurst 346 | Broadley 347 | Brock 348 | Brook 349 | Brooke 350 | Brooker 351 | Brookes 352 | Brookfield 353 | Brooks 354 | Broomfield 355 | Broughton 356 | Brown 357 | Browne 358 | Browning 359 | Bruce 360 | Brunet 361 | Brunton 362 | Bryan 363 | Bryant 364 | Bryson 365 | Buchan 366 | Buchanan 367 | Buck 368 | Buckingham 369 | Buckley 370 | Budd 371 | Bugg 372 | Bull 373 | Bullock 374 | Burch 375 | Burden 376 | Burdett 377 | Burford 378 | Burge 379 | Burgess 380 | Burke 381 | Burland 382 | Burman 383 | Burn 384 | Burnett 385 | Burns 386 | Burr 387 | Burrows 388 | Burt 389 | Burton 390 | Busby 391 | Bush 392 | Butcher 393 | Butler 394 | Butt 395 | Butter 396 | Butterworth 397 | Button 398 | Buxton 399 | Byrne 400 | Caddy 401 | Cadman 402 | Cahill 403 | Cain 404 | Cairns 405 | Caldwell 406 | Callaghan 407 | Callow 408 | Calveley 409 | Calvert 410 | Cameron 411 | Campbell 412 | Cann 413 | Cannon 414 | Caplan 415 | Capper 416 | Carey 417 | Carling 418 | Carmichael 419 | Carnegie 420 | Carney 421 | Carpenter 422 | Carr 423 | Carrington 424 | Carroll 425 | Carruthers 426 | Carson 427 | Carter 428 | Cartwright 429 | Carty 430 | Casey 431 | Cashmore 432 | Cassidy 433 | Caton 434 | Cavanagh 435 | Cawley 436 | Chadwick 437 | Chalmers 438 | Chamberlain 439 | Chambers 440 | Chan 441 | Chance 442 | Chandler 443 | Chantler 444 | Chaplin 445 | Chapman 446 | Chappell 447 | Chapple 448 | Charge 449 | Charles 450 | Charlton 451 | Charnock 452 | Chase 453 | Chatterton 454 | Chauhan 455 | Cheetham 456 | Chelmy 457 | Cherry 458 | Cheshire 459 | Chester 460 | Cheung 461 | Chidlow 462 | Child 463 | Childs 464 | Chilvers 465 | Chisholm 466 | Chong 467 | Christie 468 | Christy 469 | Chung 470 | Church 471 | Churchill 472 | Clamp 473 | Clancy 474 | Clark 475 | Clarke 476 | Clarkson 477 | Clay 478 | Clayton 479 | Cleary 480 | Cleaver 481 | Clegg 482 | Clements 483 | Cliff 484 | Clifford 485 | Clifton 486 | Close 487 | Clough 488 | Clowes 489 | Coates 490 | Coburn 491 | Cochrane 492 | Cockburn 493 | Cockle 494 | Coffey 495 | Cohen 496 | Cole 497 | Coleman 498 | Coles 499 | Coll 500 | Collard 501 | Collett 502 | Colley 503 | Collier 504 | Collingwood 505 | Collins 506 | Collinson 507 | Colman 508 | Compton 509 | Conneely 510 | Connell 511 | Connelly 512 | Connolly 513 | Connor 514 | Conrad 515 | Conroy 516 | Conway 517 | Cook 518 | Cooke 519 | Cookson 520 | Coomber 521 | Coombes 522 | Cooper 523 | Cope 524 | Copeland 525 | Copland 526 | Copley 527 | Corbett 528 | Corcoran 529 | Core 530 | Corlett 531 | Cormack 532 | Corner 533 | Cornish 534 | Cornock 535 | Corr 536 | Corrigan 537 | Cosgrove 538 | Costa 539 | Costello 540 | Cotter 541 | Cotterill 542 | Cotton 543 | Cottrell 544 | Couch 545 | Coulson 546 | Coulter 547 | Court 548 | Cousin 549 | Cousins 550 | Cove 551 | Cowan 552 | Coward 553 | Cowell 554 | Cowie 555 | Cowley 556 | Cox 557 | Coyle 558 | Crabb 559 | Crabtree 560 | Cracknell 561 | Craig 562 | Crane 563 | Craven 564 | Crawford 565 | Crawley 566 | Creasey 567 | Cresswell 568 | Crew 569 | Cripps 570 | Crisp 571 | Crocker 572 | Croft 573 | Crofts 574 | Cronin 575 | Crook 576 | Crosby 577 | Cross 578 | Crossland 579 | Crossley 580 | Crouch 581 | Croucher 582 | Crow 583 | Crowe 584 | Crowley 585 | Crown 586 | Crowther 587 | Crump 588 | Cullen 589 | Cumming 590 | Cummings 591 | Cummins 592 | Cunningham 593 | Curley 594 | Curran 595 | Currie 596 | Curry 597 | Curtis 598 | Curwood 599 | Cutts 600 | D arcy 601 | Dacey 602 | Dack 603 | Dalby 604 | Dale 605 | Daley 606 | Dallas 607 | Dalton 608 | Daly 609 | Dalzell 610 | Damon 611 | Danby 612 | Dandy 613 | Daniel 614 | Daniells 615 | Daniels 616 | Danks 617 | Dann 618 | Darby 619 | Darbyshire 620 | Darcy 621 | Dardenne 622 | Darlington 623 | Darr 624 | Daugherty 625 | Davenport 626 | Davey 627 | David 628 | Davidson 629 | Davie 630 | Davies 631 | Davis 632 | Davison 633 | Davy 634 | Dawe 635 | Dawes 636 | Dawkins 637 | Dawson 638 | Day 639 | Dayman 640 | De ath 641 | Deacon 642 | Deakin 643 | Dean 644 | Deane 645 | Deans 646 | Debenham 647 | Deegan 648 | Deeley 649 | Deighton 650 | Delamarre 651 | Delaney 652 | Dell 653 | Dempsey 654 | Dempster 655 | Denby 656 | Denham 657 | Denis 658 | Denney 659 | Dennis 660 | Dent 661 | Denton 662 | Depp 663 | Dermody 664 | Derrick 665 | Derrien 666 | Dervish 667 | Desai 668 | Devaney 669 | Devenish 670 | Deverell 671 | Devine 672 | Devlin 673 | Devon 674 | Devonport 675 | Dewar 676 | Dexter 677 | Diamond 678 | Dibble 679 | Dick 680 | Dickens 681 | Dickenson 682 | Dicker 683 | Dickinson 684 | Dickson 685 | Dillon 686 | Dimmock 687 | Dingle 688 | Dipper 689 | Dixon 690 | Dobbin 691 | Dobbins 692 | Doble 693 | Dobson 694 | Docherty 695 | Docker 696 | Dodd 697 | Dodds 698 | Dodson 699 | Doherty 700 | Dolan 701 | Dolcy 702 | Dolman 703 | Dolton 704 | Donald 705 | Donaldson 706 | Donkin 707 | Donlan 708 | Donn 709 | Donnachie 710 | Donnelly 711 | Donoghue 712 | Donohoe 713 | Donovan 714 | Dooley 715 | Doolin 716 | Doon 717 | Doors 718 | Dora 719 | Doran 720 | Dorman 721 | Dornan 722 | Dorrian 723 | Dorrington 724 | Dougal 725 | Dougherty 726 | Doughty 727 | Douglas 728 | Douthwaite 729 | Dove 730 | Dover 731 | Dowell 732 | Dowler 733 | Dowling 734 | Down 735 | Downer 736 | Downes 737 | Downey 738 | Downie 739 | Downing 740 | Downs 741 | Downton 742 | Dowson 743 | Doyle 744 | Drabble 745 | Drain 746 | Drake 747 | Draper 748 | Drew 749 | Drewett 750 | Dreyer 751 | Driffield 752 | Drinkwater 753 | Driscoll 754 | Driver 755 | Drummond 756 | Drury 757 | Drysdale 758 | Dubois 759 | Duck 760 | Duckworth 761 | Ducon 762 | Dudley 763 | Duff 764 | Duffield 765 | Duffin 766 | Duffy 767 | Dufour 768 | Duggan 769 | Duke 770 | Dukes 771 | Dumont 772 | Duncan 773 | Dundon 774 | Dunford 775 | Dunkley 776 | Dunlop 777 | Dunmore 778 | Dunn 779 | Dunne 780 | Dunnett 781 | Dunning 782 | Dunsford 783 | Dupont 784 | Durand 785 | Durant 786 | Durber 787 | Durham 788 | Durrant 789 | Dutt 790 | Duval 791 | Duvall 792 | Dwyer 793 | Dyde 794 | Dyer 795 | Dyerson 796 | Dykes 797 | Dymond 798 | Dymott 799 | Dyson 800 | Eade 801 | Eadie 802 | Eagle 803 | Eales 804 | Ealham 805 | Ealy 806 | Eames 807 | Eansworth 808 | Earing 809 | Earl 810 | Earle 811 | Earley 812 | Easdale 813 | Easdown 814 | Easen 815 | Eason 816 | East 817 | Eastaugh 818 | Eastaway 819 | Eastell 820 | Easterbrook 821 | Eastham 822 | Easton 823 | Eastwood 824 | Eatherington 825 | Eaton 826 | Eaves 827 | Ebbs 828 | Ebden 829 | Ebdon 830 | Ebeling 831 | Eburne 832 | Eccles 833 | Eccleston 834 | Ecclestone 835 | Eccott 836 | Eckersall 837 | Eckersley 838 | Eddison 839 | Eddleston 840 | Eddy 841 | Eden 842 | Edeson 843 | Edgar 844 | Edge 845 | Edgell 846 | Edgerton 847 | Edgley 848 | Edgson 849 | Edkins 850 | Edler 851 | Edley 852 | Edlington 853 | Edmond 854 | Edmonds 855 | Edmondson 856 | Edmunds 857 | Edmundson 858 | Edney 859 | Edon 860 | Edwards 861 | Edwick 862 | Eedie 863 | Egan 864 | Egerton 865 | Eggby 866 | Eggison 867 | Eggleston 868 | Eglan 869 | Egleton 870 | Eglin 871 | Eilers 872 | Ekin 873 | Elbutt 874 | Elcock 875 | Elder 876 | Eldeston 877 | Eldridge 878 | Eley 879 | Elfman 880 | Elford 881 | Elkin 882 | Elkington 883 | Ellam 884 | Ellans 885 | Ellard 886 | Elleray 887 | Ellerby 888 | Ellershaw 889 | Ellery 890 | Elliman 891 | Elling 892 | Ellingham 893 | Elliot 894 | Elliott 895 | Ellis 896 | Ellison 897 | Elliston 898 | Ellrott 899 | Ellwood 900 | Elmer 901 | Elmes 902 | Elmhirst 903 | Elmore 904 | Elms 905 | Elphick 906 | Elsdon 907 | Elsmore 908 | Elson 909 | Elston 910 | Elstone 911 | Eltis 912 | Elven 913 | Elvin 914 | Elvins 915 | Elwell 916 | Elwood 917 | Elworthy 918 | Elzer 919 | Emberey 920 | Emberson 921 | Embleton 922 | Emerick 923 | Emerson 924 | Emery 925 | Emmanuel 926 | Emmerson 927 | Emmery 928 | Emmett 929 | Emmings 930 | Emmins 931 | Emmons 932 | Emmott 933 | Emms 934 | Emsden 935 | Endroe 936 | England 937 | English 938 | Ennis 939 | Ennos 940 | Enright 941 | Enticott 942 | Entwistle 943 | Epsom 944 | Epton 945 | Ernest 946 | Erridge 947 | Errington 948 | Errity 949 | Esan 950 | Escott 951 | Eskins 952 | Eslick 953 | Espley 954 | Essam 955 | Essan 956 | Essop 957 | Estlick 958 | Etchells 959 | Etheridge 960 | Etherington 961 | Etherton 962 | Ettrick 963 | Evans 964 | Evason 965 | Evenden 966 | Everdell 967 | Everett 968 | Everill 969 | Everitt 970 | Everson 971 | Everton 972 | Eveson 973 | Evison 974 | Evrard 975 | Ewart 976 | Ewin 977 | Ewing 978 | Ewles 979 | Exley 980 | Exon 981 | Exton 982 | Eyett 983 | Eyles 984 | Eyre 985 | Eyres 986 | Fabb 987 | Fagan 988 | Fagon 989 | Fahy 990 | Fairbairn 991 | Fairbrace 992 | Fairbrother 993 | Fairchild 994 | Fairclough 995 | Fairhurst 996 | Fairley 997 | Fairlie 998 | Fairweather 999 | Falconer 1000 | Falk 1001 | Fall 1002 | Fallon 1003 | Fallows 1004 | Falsh 1005 | Farge 1006 | Fargher 1007 | Farhall 1008 | Farley 1009 | Farmer 1010 | Farnsworth 1011 | Farnum 1012 | Farnworth 1013 | Farr 1014 | Farrant 1015 | Farrar 1016 | Farre 1017 | Farrell 1018 | Farrelly 1019 | Farren 1020 | Farrer 1021 | Farrier 1022 | Farrington 1023 | Farrow 1024 | Faulkner 1025 | Faust 1026 | Fawcett 1027 | Fawn 1028 | Faye 1029 | Fearn 1030 | Fearnley 1031 | Fearns 1032 | Fearon 1033 | Featherstone 1034 | Feeney 1035 | Feetham 1036 | Felix 1037 | Fell 1038 | Fellmen 1039 | Fellows 1040 | Feltham 1041 | Felton 1042 | Fenlon 1043 | Fenn 1044 | Fenton 1045 | Fenwick 1046 | Ferdinand 1047 | Fereday 1048 | Ferguson 1049 | Fern 1050 | Fernandez 1051 | Ferns 1052 | Fernyhough 1053 | Ferreira 1054 | Ferrier 1055 | Ferris 1056 | Ferry 1057 | Fewtrell 1058 | Field 1059 | Fielder 1060 | Fielding 1061 | Fields 1062 | Fifield 1063 | Finan 1064 | Finbow 1065 | Finch 1066 | Findlay 1067 | Findley 1068 | Finlay 1069 | Finn 1070 | Finnegan 1071 | Finney 1072 | Finnigan 1073 | Finnimore 1074 | Firth 1075 | Fischer 1076 | Fish 1077 | Fisher 1078 | Fishlock 1079 | Fisk 1080 | Fitch 1081 | Fitchett 1082 | Fitton 1083 | Fitzgerald 1084 | Fitzpatrick 1085 | Fitzsimmons 1086 | Flack 1087 | Flaherty 1088 | Flanagan 1089 | Flanders 1090 | Flannery 1091 | Flavell 1092 | Flaxman 1093 | Fleetwood 1094 | Fleming 1095 | Fletcher 1096 | Flett 1097 | Florey 1098 | Floss 1099 | Flower 1100 | Flowers 1101 | Floyd 1102 | Flynn 1103 | Foden 1104 | Fogg 1105 | Foley 1106 | Fontaine 1107 | Foran 1108 | Forbes 1109 | Ford 1110 | Forde 1111 | Fordham 1112 | Foreman 1113 | Forester 1114 | Forman 1115 | Forrest 1116 | Forrester 1117 | Forshaw 1118 | Forster 1119 | Forsyth 1120 | Forsythe 1121 | Forth 1122 | Fortin 1123 | Foss 1124 | Fossard 1125 | Fosse 1126 | Foster 1127 | Foston 1128 | Fothergill 1129 | Fotheringham 1130 | Foucher 1131 | Foulkes 1132 | Fountain 1133 | Fowler 1134 | Fowley 1135 | Fox 1136 | Foxall 1137 | Foxley 1138 | Frame 1139 | Frampton 1140 | France 1141 | Francis 1142 | Franco 1143 | Frankish 1144 | Frankland 1145 | Franklin 1146 | Franks 1147 | Frary 1148 | Fraser 1149 | Frazer 1150 | Frederick 1151 | Frederikson 1152 | Freeburn 1153 | Freedman 1154 | Freeman 1155 | Freestone 1156 | Freeth 1157 | Freight 1158 | French 1159 | Fretwell 1160 | Frey 1161 | Fricker 1162 | Friel 1163 | Friend 1164 | Frith 1165 | Froggatt 1166 | Froggett 1167 | Frost 1168 | Frostick 1169 | Froy 1170 | Frusher 1171 | Fryer 1172 | Fulker 1173 | Fuller 1174 | Fulleron 1175 | Fullerton 1176 | Fulton 1177 | Funnell 1178 | Furey 1179 | Furlong 1180 | Furnell 1181 | Furness 1182 | Furnish 1183 | Furniss 1184 | Furse 1185 | Fyall 1186 | Gadsden 1187 | Gaffney 1188 | Galbraith 1189 | Gale 1190 | Gales 1191 | Gall 1192 | Gallacher 1193 | Gallagher 1194 | Galliford 1195 | Gallo 1196 | Galloway 1197 | Galvin 1198 | Gamble 1199 | Gammer 1200 | Gammon 1201 | Gander 1202 | Gandham 1203 | Ganivet 1204 | Garber 1205 | Garbett 1206 | Garbutt 1207 | Garcia 1208 | Gardener 1209 | Gardiner 1210 | Gardner 1211 | Garland 1212 | Garner 1213 | Garrard 1214 | Garratt 1215 | Garrett 1216 | Garside 1217 | Garvey 1218 | Gascoyne 1219 | Gaskell 1220 | Gately 1221 | Gates 1222 | Gaudin 1223 | Gaumont 1224 | Gauntlett 1225 | Gavin 1226 | Gaynor 1227 | Geaney 1228 | Geary 1229 | Geeson 1230 | Geldard 1231 | Geldart 1232 | Gell 1233 | Gemmell 1234 | Gene 1235 | George 1236 | Gerard 1237 | Gerrard 1238 | Geyer 1239 | Gibb 1240 | Gibbins 1241 | Gibbon 1242 | Gibbons 1243 | Gibbs 1244 | Giblin 1245 | Gibson 1246 | Gifford 1247 | Gilbert 1248 | Gilbey 1249 | Gilchrist 1250 | Gilder 1251 | Giles 1252 | Gilfillan 1253 | Gilks 1254 | Gill 1255 | Gillam 1256 | Gillan 1257 | Gillard 1258 | Gillen 1259 | Gillespie 1260 | Gillett 1261 | Gillies 1262 | Gilmartin 1263 | Gilmore 1264 | Gilmour 1265 | Ginty 1266 | Girdwood 1267 | Girling 1268 | Given 1269 | Gladwell 1270 | Glaister 1271 | Glasby 1272 | Glasgow 1273 | Glass 1274 | Gleave 1275 | Gledhill 1276 | Gleeson 1277 | Glen 1278 | Glencross 1279 | Glenn 1280 | Glennie 1281 | Glennon 1282 | Glew 1283 | Glossop 1284 | Glover 1285 | Glynn 1286 | Goble 1287 | Godby 1288 | Goddard 1289 | Godden 1290 | Godfrey 1291 | Godwin 1292 | Goff 1293 | Gold 1294 | Goldberg 1295 | Golding 1296 | Goldman 1297 | Goldsmith 1298 | Goldsworthy 1299 | Gomez 1300 | Gonzalez 1301 | Gooch 1302 | Good 1303 | Goodacre 1304 | Goodall 1305 | Goodchild 1306 | Goode 1307 | Gooding 1308 | Goodman 1309 | Goodridge 1310 | Goodson 1311 | Goodwin 1312 | Goodyear 1313 | Gordon 1314 | Goring 1315 | Gorman 1316 | Gosden 1317 | Gosling 1318 | Gough 1319 | Gould 1320 | Goulden 1321 | Goulding 1322 | Gourlay 1323 | Govender 1324 | Govier 1325 | Gower 1326 | Gowing 1327 | Grady 1328 | Graham 1329 | Grainger 1330 | Grange 1331 | Granger 1332 | Grant 1333 | Graves 1334 | Gray 1335 | Grayson 1336 | Greaves 1337 | Green 1338 | Greenall 1339 | Greenaway 1340 | Greene 1341 | Greener 1342 | Greenhill 1343 | Greening 1344 | Greenleaf 1345 | Greenshields 1346 | Greenslade 1347 | Greensmith 1348 | Greenway 1349 | Greenwood 1350 | Greer 1351 | Gregory 1352 | Greig 1353 | Grenard 1354 | Grennan 1355 | Gresham 1356 | Grey 1357 | Grierson 1358 | Griff 1359 | Griffin 1360 | Griffith 1361 | Griffiths 1362 | Griggs 1363 | Grimes 1364 | Grimshaw 1365 | Grinham 1366 | Grivet 1367 | Grogan 1368 | Groom 1369 | Grose 1370 | Grosvenor 1371 | Grout 1372 | Groves 1373 | Grundy 1374 | Guest 1375 | Guilmard 1376 | Guinard 1377 | Gulley 1378 | Gunby 1379 | Gunn 1380 | Gunning 1381 | Gunston 1382 | Gunter 1383 | Guthrie 1384 | Gutteridge 1385 | Guttridge 1386 | Hackett 1387 | Hadden 1388 | Haddock 1389 | Hadfield 1390 | Hagan 1391 | Haggett 1392 | Haigh 1393 | Haine 1394 | Haines 1395 | Hale 1396 | Halford 1397 | Hall 1398 | Hallam 1399 | Hallett 1400 | Halliday 1401 | Halliwell 1402 | Halstead 1403 | Hamer 1404 | Hamill 1405 | Hamilton 1406 | Hammond 1407 | Hamnett 1408 | Hampson 1409 | Hampton 1410 | Hancock 1411 | Hand 1412 | Handley 1413 | Hanlon 1414 | Hannam 1415 | Hansen 1416 | Hanson 1417 | Harden 1418 | Harding 1419 | Hardwick 1420 | Hardy 1421 | Hargreaves 1422 | Harker 1423 | Harkness 1424 | Harley 1425 | Harlow 1426 | Harman 1427 | Harness 1428 | Harper 1429 | Harries 1430 | Harrington 1431 | Harris 1432 | Harrison 1433 | Harrop 1434 | Harry 1435 | Hart 1436 | Hartley 1437 | Harvey 1438 | Harwood 1439 | Haslam 1440 | Hassan 1441 | Hassani 1442 | Hastings 1443 | Hatch 1444 | Hatton 1445 | Hawes 1446 | Hawker 1447 | Hawkes 1448 | Hawkins 1449 | Hawkridge 1450 | Hawley 1451 | Haworth 1452 | Hawtin 1453 | Hayes 1454 | Haynes 1455 | Hayward 1456 | Head 1457 | Healey 1458 | Healy 1459 | Heath 1460 | Heathcote 1461 | Heather 1462 | Heatley 1463 | Heaton 1464 | Hedley 1465 | Hegney 1466 | Helley 1467 | Hellier 1468 | Helm 1469 | Hemingway 1470 | Hemmings 1471 | Henderson 1472 | Hendry 1473 | Heneghan 1474 | Hennessy 1475 | Henry 1476 | Hepburn 1477 | Hepples 1478 | Herbert 1479 | Heritage 1480 | Heron 1481 | Herron 1482 | Hetherington 1483 | Hewitt 1484 | Hewlett 1485 | Heywood 1486 | Hibbert 1487 | Hickey 1488 | Hickman 1489 | Hicks 1490 | Higgins 1491 | Higginson 1492 | Higgs 1493 | Hill 1494 | Hills 1495 | Hilton 1496 | Hind 1497 | Hinde 1498 | Hindle 1499 | Hindley 1500 | Hinds 1501 | Hine 1502 | Hinton 1503 | Hirst 1504 | Hiscocks 1505 | Hitchcock 1506 | Hoare 1507 | Hobbs 1508 | Hobson 1509 | Hocking 1510 | Hodder 1511 | Hodge 1512 | Hodges 1513 | Hodgkins 1514 | Hodgkinson 1515 | Hodgson 1516 | Hodkinson 1517 | Hodson 1518 | Hogan 1519 | Hogg 1520 | Holden 1521 | Holder 1522 | Holding 1523 | Holdsworth 1524 | Hole 1525 | Holgate 1526 | Holl 1527 | Holland 1528 | Hollis 1529 | Holloway 1530 | Holman 1531 | Holmes 1532 | Holt 1533 | Homer 1534 | Hood 1535 | Hook 1536 | Hooper 1537 | Hooton 1538 | Hope 1539 | Hopes 1540 | Hopkins 1541 | Hopkinson 1542 | Hopwood 1543 | Horn 1544 | Horne 1545 | Horner 1546 | 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Ironman 1616 | Ironmonger 1617 | Irvin 1618 | Irvine 1619 | Irving 1620 | Irwin 1621 | Isaac 1622 | Isaacs 1623 | Isbill 1624 | Isbitt 1625 | Isgate 1626 | Isherwod 1627 | Isherwood 1628 | Islam 1629 | Isman 1630 | Isnard 1631 | Issac 1632 | Ivory 1633 | Izzard 1634 | Jackman 1635 | Jacks 1636 | Jackson 1637 | Jacob 1638 | Jacobs 1639 | Jacobson 1640 | Jacques 1641 | Jaffray 1642 | Jagger 1643 | Jakeman 1644 | James 1645 | Jameson 1646 | Jamieson 1647 | Janes 1648 | Jansen 1649 | Jardine 1650 | Jarman 1651 | Jarram 1652 | Jarratt 1653 | Jarrett 1654 | Jarrold 1655 | Jarvis 1656 | Jasper 1657 | Jebson 1658 | Jeffcock 1659 | Jefferies 1660 | Jeffers 1661 | Jefferson 1662 | Jeffery 1663 | Jefford 1664 | Jeffrey 1665 | Jeffreys 1666 | Jeffries 1667 | Jeffs 1668 | Jems 1669 | Jenas 1670 | Jenkin 1671 | Jenkins 1672 | Jenkinson 1673 | Jenks 1674 | Jenkyns 1675 | Jenner 1676 | Jennings 1677 | Jennison 1678 | Jennson 1679 | Jensen 1680 | Jepson 1681 | Jermy 1682 | Jerome 1683 | Jerry 1684 | Jervis 1685 | Jesson 1686 | Jessop 1687 | Jevons 1688 | Jewell 1689 | Jewers 1690 | Jewett 1691 | Jewitt 1692 | Jewkes 1693 | Jewson 1694 | Jiggens 1695 | Jobson 1696 | Johannson 1697 | Johansen 1698 | Johanson 1699 | John 1700 | Johns 1701 | Johnson 1702 | Johnston 1703 | Johnstone 1704 | Jolley 1705 | Jolly 1706 | Jonas 1707 | Jones 1708 | Jonhson 1709 | Jopson 1710 | Jordan 1711 | Jordison 1712 | Jordon 1713 | Joseph 1714 | Joss 1715 | Jourdan 1716 | Jowett 1717 | Jowitt 1718 | Joyce 1719 | Joynson 1720 | Jubb 1721 | Judd 1722 | Judge 1723 | Jukes 1724 | Jupp 1725 | Jury 1726 | Kacy 1727 | Kaddour 1728 | Kamara 1729 | Kampfner 1730 | Kane 1731 | Kanes 1732 | Kapoor 1733 | Karim 1734 | Karne 1735 | Karras 1736 | Kassell 1737 | Kaufman 1738 | Kaul 1739 | Kaur 1740 | Kavanagh 1741 | Kay 1742 | Kaye 1743 | Kayes 1744 | Keable 1745 | Keal 1746 | Kealey 1747 | Keane 1748 | Kearney 1749 | Kearns 1750 | Kearsley 1751 | Kearton 1752 | Keating 1753 | Keaveney 1754 | Keay 1755 | Keeble 1756 | Keefe 1757 | Keegan 1758 | Keelan 1759 | Keeler 1760 | Keeley 1761 | Keeling 1762 | Keenan 1763 | Keene 1764 | Keetley 1765 | Keffler 1766 | Kehoe 1767 | Keighley 1768 | Keight 1769 | Keilty 1770 | Keir 1771 | Keith 1772 | Kelk 1773 | Kell 1774 | Kelland 1775 | Kellems 1776 | Kellie 1777 | Kelliher 1778 | Kelly 1779 | Kelsall 1780 | Kelsey 1781 | Kelso 1782 | Kemp 1783 | Kempson 1784 | Kempster 1785 | Kendall 1786 | Kendell 1787 | Kendrick 1788 | Kenley 1789 | Kennard 1790 | Kennedy 1791 | Kenneford 1792 | Kennell 1793 | Kenneth 1794 | Kennett 1795 | Kenney 1796 | Kenning 1797 | Kenny 1798 | Kenrick 1799 | Kensington 1800 | Kent 1801 | Kentwood 1802 | Kenward 1803 | Kenworthy 1804 | Kenyon 1805 | Keogh 1806 | Kerby 1807 | Kernick 1808 | Kerr 1809 | Kerrell 1810 | Kerridge 1811 | Kerrigan 1812 | Kerrighen 1813 | Kerrison 1814 | Kershaw 1815 | Ketley 1816 | Kett 1817 | Kettell 1818 | Ketteringham 1819 | Kettlewell 1820 | Keward 1821 | Kewley 1822 | Keys 1823 | Keyte 1824 | Keywood 1825 | Khalid 1826 | Khalifa 1827 | Khalil 1828 | Khan 1829 | Kibblewhite 1830 | Kidd 1831 | Kiddle 1832 | Kidman 1833 | Kidner 1834 | Kiely 1835 | Kiernan 1836 | Kilb 1837 | Kilbee 1838 | Kilbey 1839 | Kilbride 1840 | Kilburn 1841 | Kilford 1842 | Kill 1843 | Killeen 1844 | Killen 1845 | Killick 1846 | Killock 1847 | Kilminster 1848 | Kilmurry 1849 | Kilnan 1850 | Kilner 1851 | Kilroy 1852 | Kilshaw 1853 | Kimber 1854 | Kimble 1855 | Kinch 1856 | Kinchin 1857 | Kinder 1858 | King 1859 | Kingdon 1860 | Kinghorn 1861 | Kingman 1862 | Kings 1863 | Kingscott 1864 | Kingsley 1865 | Kingston 1866 | Kinnaird 1867 | Kinnear 1868 | Kinnersley 1869 | Kinniburgh 1870 | Kinnison 1871 | Kinrade 1872 | Kinsella 1873 | Kinsey 1874 | Kinsley 1875 | Kipling 1876 | Kirby 1877 | Kirk 1878 | Kirkbride 1879 | Kirkbright 1880 | Kirkby 1881 | Kirkland 1882 | Kirkman 1883 | Kirkpatrick 1884 | Kirkwood 1885 | Kirtley 1886 | Kirwan 1887 | Kirwin 1888 | Kitchen 1889 | Kitchin 1890 | Kitching 1891 | Kitson 1892 | Kitt 1893 | Klam 1894 | Klein 1895 | Knab 1896 | Knappett 1897 | Knibb 1898 | Knigge 1899 | Knight 1900 | Knightley 1901 | Knighton 1902 | Knights 1903 | Knott 1904 | Knowler 1905 | Knowles 1906 | Knox 1907 | Knoxville 1908 | Knuckles 1909 | Knutt 1910 | Koban 1911 | Kolt 1912 | Kone 1913 | Kore 1914 | Kouma 1915 | Kram 1916 | Kreyling 1917 | Kristensen 1918 | Kromberg 1919 | Kruger 1920 | Kumar 1921 | Kurian 1922 | Kurray 1923 | Kydd 1924 | Kyle 1925 | Kysel 1926 | Labbe 1927 | Lacey 1928 | Lacy 1929 | Laing 1930 | Laird 1931 | Lake 1932 | Lakey 1933 | Lakin 1934 | Lamb 1935 | Lambert 1936 | Lambton 1937 | Lame 1938 | Lamond 1939 | Lancaster 1940 | Lander 1941 | Lane 1942 | Lang 1943 | Langdon 1944 | Lange 1945 | Langford 1946 | Langley 1947 | Langridge 1948 | Langston 1949 | Langton 1950 | Lanham 1951 | Laraway 1952 | Large 1953 | Larkin 1954 | Larkings 1955 | Larsen 1956 | Larsson 1957 | Last 1958 | Latham 1959 | Lathan 1960 | Lathey 1961 | Lattimore 1962 | Laurie 1963 | Laver 1964 | Laverick 1965 | Lavery 1966 | Lawal 1967 | Lawler 1968 | Lawlor 1969 | Lawn 1970 | Lawrance 1971 | Lawrence 1972 | Lawrie 1973 | Laws 1974 | Lawson 1975 | Lawther 1976 | Lawton 1977 | Laycock 1978 | Layton 1979 | Le tissier 1980 | Leach 1981 | Leadley 1982 | Leahy 1983 | Leake 1984 | Leal 1985 | Leary 1986 | Leaver 1987 | Leck 1988 | Leckie 1989 | Ledger 1990 | Lee 1991 | Leech 1992 | Leedham 1993 | Leek 1994 | Leeming 1995 | Lees 1996 | Leese 1997 | Leeson 1998 | Legg 1999 | Legge 2000 | Leggett 2001 | Leigh 2002 | Leighton 2003 | Leitch 2004 | Leith 2005 | Lendon 2006 | Lenihan 2007 | Lennard 2008 | Lennon 2009 | Lennox 2010 | Leonard 2011 | Leroy 2012 | Leslie 2013 | Lester 2014 | Lethbridge 2015 | Levann 2016 | Levett 2017 | Levin 2018 | Levine 2019 | Levy 2020 | Lewin 2021 | Lewington 2022 | Lewins 2023 | Lewis 2024 | Lewry 2025 | Leyland 2026 | Leys 2027 | Leyshon 2028 | Liddell 2029 | Liddle 2030 | Lightfoot 2031 | Lilley 2032 | Lilly 2033 | Lilwall 2034 | Lincoln 2035 | Lind 2036 | Linden 2037 | Lindo 2038 | Lindop 2039 | Lindsay 2040 | Line 2041 | Lines 2042 | Linford 2043 | Ling 2044 | Linley 2045 | Linsby 2046 | Linton 2047 | Lister 2048 | Litchfield 2049 | Little 2050 | Littlewood 2051 | Livermore 2052 | Livingstone 2053 | Llewellyn 2054 | Lloyd 2055 | Loat 2056 | Lobb 2057 | Lock 2058 | Locke 2059 | Lockett 2060 | Lockhart 2061 | Lockie 2062 | Lockwood 2063 | Lockyer 2064 | Lodge 2065 | Loft 2066 | Lofthouse 2067 | Loftus 2068 | Logan 2069 | Lohan 2070 | Lois 2071 | Lomas 2072 | Lomax 2073 | London 2074 | Long 2075 | Longhurst 2076 | Longley 2077 | Longworth 2078 | Lonsdale 2079 | Lopes 2080 | Lopez 2081 | Lord 2082 | Loudon 2083 | Loughran 2084 | Louth 2085 | Lovatt 2086 | Love 2087 | Lovegrove 2088 | Lovell 2089 | Lovelock 2090 | Lovett 2091 | Lovey 2092 | Lowbridge 2093 | Lowdon 2094 | Lowe 2095 | Lowes 2096 | Lowis 2097 | Lowndes 2098 | Lowrie 2099 | Lowry 2100 | Lucas 2101 | Luce 2102 | Lucey 2103 | Luckhurst 2104 | Ludgrove 2105 | Ludkin 2106 | Ludlow 2107 | Luke 2108 | Luker 2109 | Lumb 2110 | Lumley 2111 | Lumsden 2112 | Lunn 2113 | Lunt 2114 | Luscombe 2115 | Luttrell 2116 | Luxton 2117 | Lyall 2118 | Lyes 2119 | Lyme 2120 | Lynas 2121 | Lynch 2122 | Lynes 2123 | Lynn 2124 | Lyon 2125 | Lyons 2126 | Mac 2127 | Macarthur 2128 | Macaulay 2129 | Macdonald 2130 | Mace 2131 | Macfarlane 2132 | Macgregor 2133 | Machin 2134 | Macintyre 2135 | Mack 2136 | Mackay 2137 | Mackenzie 2138 | Mackie 2139 | Maclean 2140 | Macleod 2141 | Macmillan 2142 | Macpherson 2143 | Macrae 2144 | Madden 2145 | Maddocks 2146 | Magee 2147 | Maguire 2148 | Maher 2149 | Mahoney 2150 | Main 2151 | Mair 2152 | Major 2153 | Makin 2154 | Malley 2155 | Mallinson 2156 | Malone 2157 | Maloney 2158 | Mangnall 2159 | Mann 2160 | Manning 2161 | Mansell 2162 | Mansfield 2163 | Manson 2164 | Markham 2165 | Marks 2166 | Marlow 2167 | Marr 2168 | Marriott 2169 | Marsden 2170 | Marsh 2171 | Marshall 2172 | Martin 2173 | Martinez 2174 | Martins 2175 | Mason 2176 | Masters 2177 | Mather 2178 | Mathers 2179 | Matheson 2180 | Mathews 2181 | Matthams 2182 | Matthews 2183 | Maughan 2184 | Mawson 2185 | Maxwell 2186 | May 2187 | Maynard 2188 | Mcarthur 2189 | Mcauley 2190 | Mcavoy 2191 | Mcbain 2192 | Mccabe 2193 | Mccaffrey 2194 | Mccall 2195 | Mccallum 2196 | Mccann 2197 | Mccarthy 2198 | Mccartney 2199 | Mccluskey 2200 | Mcclymont 2201 | Mcconnell 2202 | Mccormack 2203 | Mccormick 2204 | Mccourt 2205 | Mcculloch 2206 | Mccullough 2207 | Mcdermott 2208 | Mcdonagh 2209 | Mcdonald 2210 | Mcdonnell 2211 | Mcdougall 2212 | Mcelroy 2213 | Mcewan 2214 | Mcfadden 2215 | Mcfarlane 2216 | Mcgee 2217 | Mcghee 2218 | Mcgill 2219 | Mcginty 2220 | Mcgowan 2221 | Mcgrady 2222 | Mcgrath 2223 | Mcgregor 2224 | Mcgrory 2225 | Mcguinness 2226 | Mcguire 2227 | Mcintosh 2228 | Mcintyre 2229 | Mckay 2230 | Mckee 2231 | Mckenna 2232 | Mckenzie 2233 | Mckeown 2234 | Mckie 2235 | Mclaren 2236 | Mclaughlin 2237 | Mclean 2238 | Mclellan 2239 | Mcleod 2240 | Mcloughlin 2241 | Mcmahon 2242 | Mcmanus 2243 | Mcmillan 2244 | Mcnally 2245 | Mcnamara 2246 | Mcnaught 2247 | Mcneil 2248 | Mcneill 2249 | Mcnulty 2250 | Mcphail 2251 | Mcphee 2252 | Mcpherson 2253 | Mcrae 2254 | Mcshane 2255 | Mctaggart 2256 | Meadows 2257 | Meakin 2258 | Mears 2259 | Melia 2260 | Mellor 2261 | Meredith 2262 | Merritt 2263 | Metcalf 2264 | Metcalfe 2265 | Michael 2266 | Michel 2267 | Middleton 2268 | Miles 2269 | Milford 2270 | Mill 2271 | Millar 2272 | Millard 2273 | Miller 2274 | Millett 2275 | Milligan 2276 | Millington 2277 | Mills 2278 | Millward 2279 | Milne 2280 | Milner 2281 | Milward 2282 | Mistry 2283 | Mitchell 2284 | Moffat 2285 | Mohamed 2286 | Mohammed 2287 | Molloy 2288 | Molyneux 2289 | Monaghan 2290 | Montague 2291 | Montgomery 2292 | Moody 2293 | Moon 2294 | Mooney 2295 | Moore 2296 | Moorhouse 2297 | Moran 2298 | More 2299 | Moreno 2300 | Moreton 2301 | Morgan 2302 | Moriarty 2303 | Morley 2304 | Moroney 2305 | Morris 2306 | Morrison 2307 | Morrow 2308 | Mortimer 2309 | Morton 2310 | Moseley 2311 | Moss 2312 | Mottram 2313 | Mould 2314 | Muir 2315 | Mullen 2316 | Mulligan 2317 | Mullins 2318 | Mundy 2319 | Munro 2320 | Murphy 2321 | Murray 2322 | Murrell 2323 | Mustafa 2324 | Myatt 2325 | Myers 2326 | Nair 2327 | Nairn 2328 | Nandi 2329 | Nanson 2330 | Nanton 2331 | Napier 2332 | Napper 2333 | Nartey 2334 | Nash 2335 | Nason 2336 | Naughton 2337 | Naumann 2338 | Nayler 2339 | Naylor 2340 | Naysmith 2341 | Neal 2342 | Neale 2343 | Neary 2344 | Neave 2345 | Neaverson 2346 | Nedd 2347 | Needham 2348 | Neeson 2349 | Negros 2350 | Neighbour 2351 | Neill 2352 | Neilsen 2353 | Neilson 2354 | Neish 2355 | Nelmes 2356 | Nelms 2357 | Nelson 2358 | Nemeth 2359 | Nero 2360 | Nesbitt 2361 | Ness 2362 | Nessbert 2363 | Nettleton 2364 | Neville 2365 | Nevins 2366 | Nevis 2367 | Newall 2368 | Newberry 2369 | Newbold 2370 | Newbury 2371 | Newby 2372 | Newcombe 2373 | Newell 2374 | Newey 2375 | Newham 2376 | Newill 2377 | Newington 2378 | Newland 2379 | Newlands 2380 | Newman 2381 | Newsham 2382 | Newsome 2383 | Newson 2384 | Newstead 2385 | Newton 2386 | Neyland 2387 | Nichol 2388 | Nicholas 2389 | Nicholl 2390 | Nicholls 2391 | Nichols 2392 | Nicholson 2393 | Nickel 2394 | Nickolls 2395 | Nicks 2396 | Nicol 2397 | Nicolas 2398 | Nicoll 2399 | Nicolson 2400 | Nield 2401 | Nielsen 2402 | Nielson 2403 | Nightingale 2404 | Niles 2405 | Nilsen 2406 | Nineham 2407 | Nisbet 2408 | Nixon 2409 | Noach 2410 | Noakes 2411 | Nobbs 2412 | Noble 2413 | Noggins 2414 | Nokes 2415 | Nolan 2416 | Nood 2417 | Noon 2418 | Noonan 2419 | Norbert 2420 | Norburn 2421 | Norbury 2422 | Norcross 2423 | Nord 2424 | Norgate 2425 | Norgrove 2426 | Norm 2427 | Norman 2428 | Normington 2429 | Norris 2430 | Norsworthy 2431 | North 2432 | Northcott 2433 | Norton 2434 | Norville 2435 | Norwood 2436 | Notman 2437 | Nott 2438 | Nourse 2439 | Nova 2440 | Nowak 2441 | Nowell 2442 | Noyce 2443 | Noyes 2444 | Nugent 2445 | Number 2446 | Nunn 2447 | Nurse 2448 | Nurton 2449 | Nutella 2450 | Nutman 2451 | Nutt 2452 | Nuttall 2453 | Oakes 2454 | Oakey 2455 | Oakley 2456 | Oaks 2457 | Oakton 2458 | Oates 2459 | Oatridge 2460 | Oatway 2461 | Obrien 2462 | Ocallaghan 2463 | Oconnell 2464 | Oconnor 2465 | Odam 2466 | Oddie 2467 | Oddy 2468 | Odea 2469 | Odell 2470 | Odling 2471 | Odonnell 2472 | Odonoghue 2473 | Odriscoll 2474 | Oflynn 2475 | Ogden 2476 | Ogilvie 2477 | Ogilvy 2478 | Ogrady 2479 | Ohalloran 2480 | Ohara 2481 | Okeefe 2482 | Okey 2483 | Okten 2484 | Olan 2485 | Oldfield 2486 | Oldham 2487 | Olding 2488 | Oldland 2489 | Oldroyd 2490 | Olds 2491 | Oleary 2492 | Oliver 2493 | Olivier 2494 | Ollerhead 2495 | Olley 2496 | Oloughlin 2497 | Olsen 2498 | Olson 2499 | Omalley 2500 | Oman 2501 | Oneil 2502 | Oneill 2503 | Opayne 2504 | Openshaw 2505 | Oram 2506 | Orbell 2507 | Orchard 2508 | Oreilly 2509 | Oriley 2510 | Orman 2511 | Orme 2512 | Ormiston 2513 | Ormond 2514 | Ormsby 2515 | Ormston 2516 | Orrell 2517 | Orritt 2518 | Orton 2519 | Orvis 2520 | Orwin 2521 | Osborn 2522 | Osborne 2523 | Osman 2524 | Osmond 2525 | Ostcliffe 2526 | Ostler 2527 | Osullivan 2528 | Oswald 2529 | Otoole 2530 | Otten 2531 | Otter 2532 | Ottey 2533 | Ottley 2534 | Otton 2535 | Ould 2536 | Oulton 2537 | Overall 2538 | Overett 2539 | Overfield 2540 | Overing 2541 | Overson 2542 | Overton 2543 | Owen 2544 | Owens 2545 | Owings 2546 | Oxby 2547 | Oxenham 2548 | Oxley 2549 | Oxtoby 2550 | Pack 2551 | Packard 2552 | Packer 2553 | Pagan 2554 | Page 2555 | Paige 2556 | Pailing 2557 | Paine 2558 | Painter 2559 | Paisley 2560 | Palfrey 2561 | Palfreyman 2562 | Palin 2563 | Pallett 2564 | Palmer 2565 | Panesar 2566 | Pankhurst 2567 | Pannell 2568 | Parish 2569 | Park 2570 | Parker 2571 | Parkes 2572 | Parkin 2573 | Parkins 2574 | Parkinson 2575 | Parks 2576 | Parmar 2577 | Parnaby 2578 | Parnell 2579 | Parr 2580 | Parratt 2581 | Parrott 2582 | Parry 2583 | Parsons 2584 | Partington 2585 | Partlett 2586 | Partridge 2587 | Pascoe 2588 | Pasfield 2589 | Paskell 2590 | Passmore 2591 | Patchett 2592 | Patel 2593 | Pateman 2594 | Paterson 2595 | Paton 2596 | Patrick 2597 | Patten 2598 | Patterson 2599 | Pattinson 2600 | Pattison 2601 | Patton 2602 | Paul 2603 | Pavot 2604 | Pawson 2605 | Payne 2606 | Peace 2607 | Peach 2608 | Peacock 2609 | Peake 2610 | Peal 2611 | Peaper 2612 | Pearce 2613 | Pears 2614 | Pearson 2615 | Peat 2616 | Peck 2617 | Pedley 2618 | Peebles 2619 | Peel 2620 | Peers 2621 | Pegg 2622 | Peigne 2623 | Pell 2624 | Pelling 2625 | Pemberton 2626 | Pender 2627 | Pendlebury 2628 | Pendleton 2629 | Penfold 2630 | Penn 2631 | Pennell 2632 | Penney 2633 | Pennington 2634 | Percival 2635 | Pereira 2636 | Perez 2637 | Perkin 2638 | Perkins 2639 | Perks 2640 | Perowne 2641 | Perrett 2642 | Perrin 2643 | Perrins 2644 | Perry 2645 | Peters 2646 | Petersen 2647 | Peterson 2648 | Petrova 2649 | Pett 2650 | Petticrew 2651 | Peyton 2652 | Phelan 2653 | Phelps 2654 | Philip 2655 | Philips 2656 | Phillips 2657 | Philpott 2658 | Phipps 2659 | Phoenix 2660 | Pick 2661 | Pickard 2662 | Pickering 2663 | Pickersgill 2664 | Pickett 2665 | Pickford 2666 | Pickthall 2667 | Picot 2668 | Pierce 2669 | Piercey 2670 | Pierre 2671 | Pigott 2672 | Pike 2673 | Pilkington 2674 | Pillay 2675 | Pinder 2676 | Pine 2677 | Pinkney 2678 | Pinner 2679 | Pinnock 2680 | Pinsmail 2681 | Pipe 2682 | Piper 2683 | Pitcher 2684 | Pitchford 2685 | Pitt 2686 | Pitts 2687 | Plant 2688 | Plastow 2689 | Platt 2690 | Platts 2691 | Pledger 2692 | Plouvin 2693 | Plumb 2694 | Plummer 2695 | Pocock 2696 | Pointer 2697 | Pole 2698 | Pollard 2699 | Pollock 2700 | Polson 2701 | Pomeroy 2702 | Pomphrey 2703 | Pond 2704 | Pooke 2705 | Poole 2706 | Poon 2707 | Pope 2708 | Porter 2709 | Potter 2710 | Potts 2711 | Poulter 2712 | Poulton 2713 | Pounder 2714 | Povey 2715 | Powell 2716 | Power 2717 | Powers 2718 | Powis 2719 | Powles 2720 | Poyser 2721 | Pratt 2722 | Preece 2723 | Prendergast 2724 | Prentice 2725 | Prescott 2726 | Preston 2727 | Prevost 2728 | Price 2729 | Prime 2730 | Prince 2731 | Pringle 2732 | Prior 2733 | Pritchard 2734 | Privett 2735 | Probert 2736 | Procter 2737 | Proctor 2738 | Prosser 2739 | Provan 2740 | Pryor 2741 | Pugh 2742 | Pullen 2743 | Purcell 2744 | Purkis 2745 | Purnell 2746 | Purse 2747 | Purvis 2748 | Putt 2749 | Pyle 2750 | Quigley 2751 | Quinlivan 2752 | Quinn 2753 | Quinnell 2754 | Quinton 2755 | Quirk 2756 | Quirke 2757 | Rackham 2758 | Radcliffe 2759 | Radford 2760 | Radley 2761 | Raeburn 2762 | Rafferty 2763 | Rahman 2764 | Raine 2765 | Rainey 2766 | Rainford 2767 | Ralph 2768 | Ralston 2769 | Ramm 2770 | Rampling 2771 | Ramsay 2772 | Ramsden 2773 | Ramsey 2774 | Rand 2775 | Randall 2776 | Randle 2777 | Ranger 2778 | Rankin 2779 | Ranks 2780 | Rann 2781 | Ransom 2782 | Ranson 2783 | Rapson 2784 | Rashid 2785 | Ratcliffe 2786 | Raval 2787 | Raven 2788 | Ravenscroft 2789 | Rawlings 2790 | Rawlinson 2791 | Rawsthorne 2792 | Raymond 2793 | Rayner 2794 | Read 2795 | Reade 2796 | Reader 2797 | Reading 2798 | Readle 2799 | Readman 2800 | Reardon 2801 | Reasbeck 2802 | Reay 2803 | Redden 2804 | Redding 2805 | Reddy 2806 | Redfern 2807 | Redhead 2808 | Redin 2809 | Redman 2810 | Redmond 2811 | Redwood 2812 | Reed 2813 | Rees 2814 | Reese 2815 | Reeve 2816 | Reeves 2817 | Regan 2818 | Regent 2819 | Rehman 2820 | Reid 2821 | Reilly 2822 | Reisser 2823 | Render 2824 | Renna 2825 | Rennalls 2826 | Rennie 2827 | Renshaw 2828 | Renwick 2829 | Reveley 2830 | Reyes 2831 | Reygan 2832 | Reynolds 2833 | Rhoades 2834 | Rhodes 2835 | Rhys 2836 | Ricci 2837 | Rice 2838 | Rich 2839 | Richards 2840 | Richardson 2841 | Riches 2842 | Richman 2843 | Richmond 2844 | Richter 2845 | Rick 2846 | Rickard 2847 | Rickards 2848 | Rickett 2849 | Ricketts 2850 | Riddell 2851 | Riddle 2852 | Riddler 2853 | Ridge 2854 | Ridgway 2855 | Ridgwell 2856 | Ridle 2857 | Ridley 2858 | Rigby 2859 | Rigg 2860 | Rigley 2861 | Riley 2862 | Ring 2863 | Ripley 2864 | Rippin 2865 | Riseborough 2866 | Ritchie 2867 | Rivers 2868 | Rixon 2869 | Roach 2870 | Robb 2871 | Robbins 2872 | Robe 2873 | Robert 2874 | Roberts 2875 | Robertson 2876 | Robin 2877 | Robins 2878 | Robinson 2879 | Robishaw 2880 | Robotham 2881 | Robson 2882 | Roche 2883 | Rochford 2884 | Rockliffe 2885 | Rodden 2886 | Roden 2887 | Rodger 2888 | Rodgers 2889 | Rodham 2890 | Rodrigues 2891 | Rodriguez 2892 | Rodwell 2893 | Roebuck 2894 | Roff 2895 | Roffey 2896 | Rogan 2897 | Rogers 2898 | Rogerson 2899 | Roles 2900 | Rolfe 2901 | Rollinson 2902 | Roman 2903 | Romans 2904 | Ronald 2905 | Ronflard 2906 | Rook 2907 | Rooke 2908 | Roome 2909 | Rooney 2910 | Rootham 2911 | Roper 2912 | Ropple 2913 | Roscoe 2914 | Rose 2915 | Rosenblatt 2916 | Rosenbloom 2917 | Ross 2918 | Rosser 2919 | Rossi 2920 | Rosso 2921 | Roth 2922 | Rothery 2923 | Rothwell 2924 | Rouse 2925 | Roussel 2926 | Rousset 2927 | Routledge 2928 | Rowan 2929 | Rowe 2930 | Rowland 2931 | Rowlands 2932 | Rowley 2933 | Rowlinson 2934 | Rowson 2935 | Royall 2936 | Royle 2937 | Rudd 2938 | Ruff 2939 | Rugg 2940 | Rumbold 2941 | Rumsey 2942 | Ruscoe 2943 | Rush 2944 | Rushbrooke 2945 | Rushby 2946 | Rushton 2947 | Russel 2948 | Russell 2949 | Russon 2950 | Rust 2951 | Rutherford 2952 | Rutter 2953 | Ryan 2954 | Ryans 2955 | Rycroft 2956 | Ryder 2957 | Sadiq 2958 | Sadler 2959 | Said 2960 | Saleh 2961 | Salisbury 2962 | Sallis 2963 | Salmon 2964 | Salt 2965 | Salter 2966 | Sampson 2967 | Samuel 2968 | Samuels 2969 | Sanchez 2970 | Sanders 2971 | Sanderson 2972 | Sandison 2973 | Sands 2974 | Santos 2975 | Sargent 2976 | Saunders 2977 | Savage 2978 | Saville 2979 | Sawyer 2980 | Saxton 2981 | Sayers 2982 | Schmid 2983 | Schmidt 2984 | Schofield 2985 | Scott 2986 | Searle 2987 | Seddon 2988 | Seer 2989 | Selby 2990 | Sellars 2991 | Sellers 2992 | Senior 2993 | Sewell 2994 | Sexton 2995 | Seymour 2996 | Shackleton 2997 | Shah 2998 | Shakespeare 2999 | Shand 3000 | Shanks 3001 | Shannon 3002 | Sharkey 3003 | Sharma 3004 | Sharp 3005 | Sharpe 3006 | Sharples 3007 | Shaughnessy 3008 | Shaw 3009 | Shea 3010 | Shearer 3011 | Sheehan 3012 | Sheldon 3013 | Shelton 3014 | Shepherd 3015 | Sheppard 3016 | Sheridan 3017 | Sherman 3018 | Sherriff 3019 | Sherry 3020 | Sherwood 3021 | Shields 3022 | Shipley 3023 | Short 3024 | Shotton 3025 | Showell 3026 | Shuttleworth 3027 | Silcock 3028 | Silva 3029 | Simmonds 3030 | Simmons 3031 | Simms 3032 | Simon 3033 | Simons 3034 | Simpson 3035 | Sims 3036 | Sinclair 3037 | Singh 3038 | Singleton 3039 | Sinha 3040 | Sisson 3041 | Sissons 3042 | Skelly 3043 | Skelton 3044 | Skinner 3045 | Skipper 3046 | Slade 3047 | Slater 3048 | Slattery 3049 | Sloan 3050 | Slocombe 3051 | Small 3052 | Smallwood 3053 | Smart 3054 | Smit 3055 | Smith 3056 | Smithson 3057 | Smullen 3058 | Smyth 3059 | Smythe 3060 | Sneddon 3061 | Snell 3062 | Snelling 3063 | Snow 3064 | Snowden 3065 | Snowdon 3066 | Somerville 3067 | South 3068 | Southern 3069 | Southgate 3070 | Southwick 3071 | Sparkes 3072 | Sparrow 3073 | Spears 3074 | Speed 3075 | Speight 3076 | Spence 3077 | Spencer 3078 | Spicer 3079 | Spiller 3080 | Spinks 3081 | Spooner 3082 | Squire 3083 | Squires 3084 | Stacey 3085 | Stack 3086 | Staff 3087 | Stafford 3088 | Stainton 3089 | Stamp 3090 | Stanfield 3091 | Stanford 3092 | Stanley 3093 | Stannard 3094 | Stanton 3095 | Stark 3096 | Steadman 3097 | Stedman 3098 | Steel 3099 | Steele 3100 | Steer 3101 | Steere 3102 | Stenhouse 3103 | Stephen 3104 | Stephens 3105 | Stephenson 3106 | Sterling 3107 | Stevens 3108 | Stevenson 3109 | Steward 3110 | Stewart 3111 | Stock 3112 | Stocker 3113 | Stockley 3114 | Stoddart 3115 | Stokes 3116 | Stokoe 3117 | Stone 3118 | Stoppard 3119 | Storer 3120 | Storey 3121 | Storr 3122 | Stott 3123 | Stout 3124 | Strachan 3125 | Strange 3126 | Street 3127 | Stretton 3128 | Strickland 3129 | Stringer 3130 | Strong 3131 | Stroud 3132 | Stuart 3133 | Stubbs 3134 | Stuckey 3135 | Sturgess 3136 | Sturrock 3137 | Styles 3138 | Sugden 3139 | Sullivan 3140 | Summers 3141 | Sumner 3142 | Sunderland 3143 | Sutherland 3144 | Sutton 3145 | Swain 3146 | Swales 3147 | Swan 3148 | Swann 3149 | Swanson 3150 | Sweeney 3151 | Sweeting 3152 | Swift 3153 | Sykes 3154 | Sylvester 3155 | Symes 3156 | Symonds 3157 | Taggart 3158 | Tailor 3159 | Tait 3160 | Talbot 3161 | Tallett 3162 | Tamber 3163 | Tang 3164 | Tanner 3165 | Tansey 3166 | Tansley 3167 | Tappin 3168 | Tapping 3169 | Tapscott 3170 | Tarr 3171 | Tarrant 3172 | Tasker 3173 | Tate 3174 | Tatlock 3175 | Tatlow 3176 | Tatnell 3177 | Taurel 3178 | Tayler 3179 | Taylor 3180 | Teague 3181 | Teal 3182 | Teale 3183 | Teasdale 3184 | Tedd 3185 | Telford 3186 | Tell 3187 | Tellis 3188 | Tempest 3189 | Templar 3190 | Temple 3191 | Templeman 3192 | Templeton 3193 | Tennant 3194 | Terry 3195 | Thackeray 3196 | Thackray 3197 | Thake 3198 | Thatcher 3199 | Thelwell 3200 | Thirlwall 3201 | Thirlway 3202 | Thirlwell 3203 | Thistlethwaite 3204 | Thom 3205 | Thomas 3206 | Thomason 3207 | Thompson 3208 | Thoms 3209 | Thomson 3210 | Thonon 3211 | Thorley 3212 | Thorndyke 3213 | Thorne 3214 | Thornes 3215 | Thornhill 3216 | Thornley 3217 | Thornton 3218 | Thorp 3219 | Thorpe 3220 | Thurbon 3221 | Thurgood 3222 | Thurling 3223 | Thurlow 3224 | Thurman 3225 | Thurston 3226 | Tickner 3227 | Tidmarsh 3228 | Tierney 3229 | Till 3230 | Tillett 3231 | Tilley 3232 | Tilson 3233 | Tilston 3234 | Timberlake 3235 | Timmins 3236 | Timms 3237 | Timney 3238 | Timson 3239 | Tindall 3240 | Tindell 3241 | Tinker 3242 | Tinkler 3243 | Tinsley 3244 | Tipping 3245 | Tippins 3246 | Tips 3247 | Tisdall 3248 | Titmarsh 3249 | Titmus 3250 | Titmuss 3251 | Titterington 3252 | Toal 3253 | Tobin 3254 | Tocher 3255 | Todd 3256 | Tohill 3257 | Toland 3258 | Tolley 3259 | Tollis 3260 | Tolmay 3261 | Tomas 3262 | Tombs 3263 | Tomes 3264 | Tomkins 3265 | Tomlin 3266 | Tomlinson 3267 | Tompkin 3268 | Tompkins 3269 | Toms 3270 | Tong 3271 | Tonge 3272 | Tonks 3273 | Tonner 3274 | Toomer 3275 | Toomey 3276 | Topham 3277 | Topley 3278 | Topliss 3279 | Topp 3280 | Torney 3281 | Torrance 3282 | Torrens 3283 | Torres 3284 | Tosh 3285 | Totten 3286 | Toucet 3287 | Tovar 3288 | Tovey 3289 | Towell 3290 | Towers 3291 | Towle 3292 | Townend 3293 | Towns 3294 | Townsend 3295 | Townsley 3296 | Tozer 3297 | Trafford 3298 | Train 3299 | Trainor 3300 | Trattles 3301 | Travers 3302 | Travill 3303 | Travis 3304 | Traynor 3305 | Treble 3306 | Trennery 3307 | Trent 3308 | Treseder 3309 | Trevor 3310 | Trew 3311 | Trickett 3312 | Trigg 3313 | Trimble 3314 | Trinder 3315 | Trollope 3316 | Troon 3317 | Trotman 3318 | Trott 3319 | Trueman 3320 | Truman 3321 | Trump 3322 | Truscott 3323 | Tuck 3324 | Tucker 3325 | Tuckey 3326 | Tudor 3327 | Tuffnell 3328 | Tufnall 3329 | Tugwell 3330 | Tully 3331 | Tunks 3332 | Tunstall 3333 | Turford 3334 | Turke 3335 | Turkington 3336 | Turland 3337 | Turnbull 3338 | Turner 3339 | Turney 3340 | Turnham 3341 | Turnock 3342 | Turrell 3343 | Turton 3344 | Turvey 3345 | Tuthill 3346 | Tuttle 3347 | Tutton 3348 | Tweddle 3349 | Twigg 3350 | Twiggs 3351 | Twine 3352 | Tyler 3353 | Tyman 3354 | Tyne 3355 | Tyrer 3356 | Tyrrell 3357 | Uddin 3358 | Ullman 3359 | Ullmann 3360 | Ulyatt 3361 | Umney 3362 | Underdown 3363 | Underhill 3364 | Underwood 3365 | Unsworth 3366 | Unwin 3367 | Upfield 3368 | Upjohn 3369 | Upsdell 3370 | Upson 3371 | Upton 3372 | Urwin 3373 | Utley 3374 | Utterson 3375 | Uttley 3376 | Utton 3377 | Uttridge 3378 | Vale 3379 | Valentine 3380 | Vallance 3381 | Vallins 3382 | Vallory 3383 | Valmary 3384 | Vancoller 3385 | Vane 3386 | Vann 3387 | Vanstone 3388 | Vanwell 3389 | Vardy 3390 | Varey 3391 | Varley 3392 | Varndell 3393 | Vass 3394 | Vaughan 3395 | Vaughn 3396 | Veale 3397 | Veasey 3398 | Veevers 3399 | Veitch 3400 | Velds 3401 | Venables 3402 | Ventura 3403 | Verdon 3404 | Verell 3405 | Verney 3406 | Vernon 3407 | Vicary 3408 | Vicens 3409 | Vickars 3410 | Vickerman 3411 | Vickers 3412 | Vickery 3413 | Victor 3414 | Vikers 3415 | Villiger 3416 | Villis 3417 | Vince 3418 | Vincent 3419 | Vine 3420 | Viner 3421 | Vines 3422 | Viney 3423 | Vinicombe 3424 | Vinny 3425 | Vinton 3426 | Virgo 3427 | Voakes 3428 | Vockins 3429 | Vodden 3430 | Vollans 3431 | Voyse 3432 | Vyner 3433 | Wade 3434 | Wadham 3435 | Waghorn 3436 | Wagstaff 3437 | Wain 3438 | Wainwright 3439 | Waite 3440 | Wakefield 3441 | Wakeford 3442 | Wakeham 3443 | Wakelin 3444 | Waldron 3445 | Wale 3446 | Wales 3447 | Walkden 3448 | Walker 3449 | Wall 3450 | Wallace 3451 | Waller 3452 | Walling 3453 | Wallis 3454 | Walls 3455 | Walmsley 3456 | Walpole 3457 | Walsh 3458 | Walshe 3459 | Walter 3460 | Walters 3461 | Walton 3462 | Wane 3463 | Wang 3464 | Warburton 3465 | Warby 3466 | Ward 3467 | Warden 3468 | Wardle 3469 | Ware 3470 | Wareing 3471 | Waring 3472 | Warn 3473 | Warner 3474 | Warren 3475 | Warriner 3476 | Warrington 3477 | Warwick 3478 | Water 3479 | Waterfield 3480 | Waterhouse 3481 | Wateridge 3482 | Waterman 3483 | Waters 3484 | Waterson 3485 | Watkins 3486 | Watkinson 3487 | Watling 3488 | Watson 3489 | Watt 3490 | Watters 3491 | Watts 3492 | Waugh 3493 | Wears 3494 | Weasley 3495 | Weaver 3496 | Webb 3497 | Webber 3498 | Webster 3499 | Weeks 3500 | Weir 3501 | Welch 3502 | Weldon 3503 | Weller 3504 | Wellington 3505 | Wellman 3506 | Wells 3507 | Welsh 3508 | Welton 3509 | Were 3510 | Werner 3511 | Werrett 3512 | West 3513 | Western 3514 | Westgate 3515 | Westlake 3516 | Weston 3517 | Westwell 3518 | Westwood 3519 | Whalley 3520 | Wharton 3521 | Wheatcroft 3522 | Wheatley 3523 | Wheeldon 3524 | Wheeler 3525 | Whelan 3526 | Whitaker 3527 | Whitby 3528 | White 3529 | Whiteford 3530 | Whitehead 3531 | Whitehouse 3532 | Whitelaw 3533 | Whiteley 3534 | Whitfield 3535 | Whitham 3536 | Whiting 3537 | Whitley 3538 | Whitlock 3539 | Whitmore 3540 | Whittaker 3541 | Whittingham 3542 | Whittington 3543 | Whittle 3544 | Whittley 3545 | Whitworth 3546 | Whyte 3547 | Wickens 3548 | Wickham 3549 | Wicks 3550 | Widdows 3551 | Widdowson 3552 | Wiggins 3553 | Wigley 3554 | Wilcox 3555 | Wild 3556 | Wilde 3557 | Wildman 3558 | Wileman 3559 | Wiles 3560 | Wilkes 3561 | Wilkie 3562 | Wilkin 3563 | Wilkins 3564 | Wilkinson 3565 | Wilks 3566 | Wilkshire 3567 | Will 3568 | Willett 3569 | Willetts 3570 | Williams 3571 | Williamson 3572 | Willis 3573 | Wills 3574 | Willson 3575 | Wilmot 3576 | Wilson 3577 | Wilton 3578 | Wiltshire 3579 | Winder 3580 | Windsor 3581 | Winfer 3582 | Winfield 3583 | Winman 3584 | Winn 3585 | Winship 3586 | Winstanley 3587 | Winter 3588 | Wintersgill 3589 | Winward 3590 | Wise 3591 | Wiseman 3592 | Wither 3593 | Withers 3594 | Wolf 3595 | Wolfe 3596 | Wolstencroft 3597 | Wong 3598 | Wood 3599 | Woodcock 3600 | Woodford 3601 | Woodhall 3602 | Woodham 3603 | Woodhams 3604 | Woodhead 3605 | Woodhouse 3606 | Woodland 3607 | Woodley 3608 | Woods 3609 | Woodward 3610 | Wooldridge 3611 | Woollard 3612 | Woolley 3613 | Woolnough 3614 | Wootton 3615 | Worgan 3616 | Wormald 3617 | Worrall 3618 | Worsnop 3619 | Worth 3620 | Worthington 3621 | Wotherspoon 3622 | Wragg 3623 | Wraight 3624 | Wray 3625 | Wren 3626 | Wrench 3627 | Wrenn 3628 | Wrigglesworth 3629 | Wright 3630 | Wrightson 3631 | Wyatt 3632 | Wyer 3633 | Yabsley 3634 | Yallop 3635 | Yang 3636 | Yapp 3637 | Yard 3638 | Yardley 3639 | Yarker 3640 | Yarlett 3641 | Yarnall 3642 | Yarnold 3643 | Yarwood 3644 | Yasmin 3645 | Yates 3646 | Yeadon 3647 | Yeardley 3648 | Yeardsley 3649 | Yeates 3650 | Yeatman 3651 | Yeldon 3652 | Yeoman 3653 | Yeomans 3654 | Yetman 3655 | Yeung 3656 | Yoman 3657 | Yomkins 3658 | York 3659 | Yorke 3660 | Yorston 3661 | Youlden 3662 | Young 3663 | Younge 3664 | Younis 3665 | Youssouf 3666 | Yule 3667 | Yusuf 3668 | Zaoui 3669 | -------------------------------------------------------------------------------- /data/names/French.txt: -------------------------------------------------------------------------------- 1 | Abel 2 | Abraham 3 | Adam 4 | Albert 5 | Allard 6 | Archambault 7 | Armistead 8 | Arthur 9 | Augustin 10 | Babineaux 11 | Baudin 12 | Beauchene 13 | Beaulieu 14 | Beaumont 15 | Bélanger 16 | Bellamy 17 | Bellerose 18 | Belrose 19 | Berger 20 | Béringer 21 | Bernard 22 | Bertrand 23 | Bisset 24 | Bissette 25 | Blaise 26 | Blanc 27 | Blanchet 28 | Blanchett 29 | Bonfils 30 | Bonheur 31 | Bonhomme 32 | Bonnaire 33 | Bonnay 34 | Bonner 35 | Bonnet 36 | Borde 37 | Bordelon 38 | Bouchard 39 | Boucher 40 | Brisbois 41 | Brodeur 42 | Bureau 43 | Caron 44 | Cavey 45 | Chaput 46 | Charbonneau 47 | Charpentier 48 | Charron 49 | Chastain 50 | Chevalier 51 | Chevrolet 52 | Cloutier 53 | Colbert 54 | Comtois 55 | Cornett 56 | Coté 57 | Coupe 58 | Courtemanche 59 | Cousineau 60 | Couture 61 | Daniau 62 | D'aramitz 63 | Daviau 64 | David 65 | Deforest 66 | Degarmo 67 | Delacroix 68 | De la fontaine 69 | Deniau 70 | Deniaud 71 | Deniel 72 | Denis 73 | De sauveterre 74 | Deschamps 75 | Descoteaux 76 | Desjardins 77 | Desrochers 78 | Desrosiers 79 | Dubois 80 | Duchamps 81 | Dufort 82 | Dufour 83 | Duguay 84 | Dupond 85 | Dupont 86 | Durand 87 | Durant 88 | Duval 89 | Émile 90 | Eustis 91 | Fabian 92 | Fabre 93 | Fabron 94 | Faucher 95 | Faucheux 96 | Faure 97 | Favager 98 | Favre 99 | Favreau 100 | Fay 101 | Félix 102 | Firmin 103 | Fontaine 104 | Forest 105 | Forestier 106 | Fortier 107 | Foss 108 | Fournier 109 | Gage 110 | Gagne 111 | Gagnier 112 | Gagnon 113 | Garcon 114 | Gardinier 115 | Germain 116 | Géroux 117 | Giles 118 | Girard 119 | Giroux 120 | Glaisyer 121 | Gosse 122 | Gosselin 123 | Granger 124 | Guérin 125 | Guillory 126 | Hardy 127 | Harman 128 | Hébert 129 | Herbert 130 | Herriot 131 | Jacques 132 | Janvier 133 | Jordan 134 | Joubert 135 | Labelle 136 | Lachance 137 | Lachapelle 138 | Lamar 139 | Lambert 140 | Lane 141 | Langlais 142 | Langlois 143 | Lapointe 144 | Larue 145 | Laurent 146 | Lavigne 147 | Lavoie 148 | Leandres 149 | Lebeau 150 | Leblanc 151 | Leclair 152 | Leclerc 153 | Lécuyer 154 | Lefebvre 155 | Lefévre 156 | Lefurgey 157 | Legrand 158 | Lemaire 159 | Lémieux 160 | Leon 161 | Leroy 162 | Lesauvage 163 | Lestrange 164 | Lévêque 165 | Lévesque 166 | Linville 167 | Lyon 168 | Lyon 169 | Maçon 170 | Marchand 171 | Marie 172 | Marion 173 | Martel 174 | Martel 175 | Martin 176 | Masson 177 | Masson 178 | Mathieu 179 | Mercier 180 | Merle 181 | Michaud 182 | Michel 183 | Monet 184 | Monette 185 | Montagne 186 | Moreau 187 | Moulin 188 | Mullins 189 | Noel 190 | Oliver 191 | Olivier 192 | Page 193 | Paget 194 | Palomer 195 | Pan 196 | Pape 197 | Paquet 198 | Paquet 199 | Parent 200 | Paris 201 | Parris 202 | Pascal 203 | Patenaude 204 | Paternoster 205 | Paul 206 | Pelletier 207 | Perrault 208 | Perreault 209 | Perrot 210 | Petit 211 | Pettigrew 212 | Pierre 213 | Plamondon 214 | Plourde 215 | Poingdestre 216 | Poirier 217 | Porcher 218 | Poulin 219 | Proulx 220 | Renaud 221 | Rey 222 | Reyer 223 | Richard 224 | Richelieu 225 | Robert 226 | Roche 227 | Rome 228 | Romilly 229 | Rose 230 | Rousseau 231 | Roux 232 | Roy 233 | Royer 234 | Salomon 235 | Salvage 236 | Samson 237 | Samuel 238 | Sargent 239 | Sarkozi 240 | Sarkozy 241 | Sartre 242 | Sault 243 | Sauvage 244 | Sauvageau 245 | Sauvageon 246 | Sauvageot 247 | Sauveterre 248 | Savatier 249 | Segal 250 | Sergeant 251 | Séverin 252 | Simon 253 | Solomon 254 | Soucy 255 | St martin 256 | St pierre 257 | Tailler 258 | Tasse 259 | Thayer 260 | Thibault 261 | Thomas 262 | Tobias 263 | Tolbert 264 | Traver 265 | Travere 266 | Travers 267 | Traverse 268 | Travert 269 | Tremblay 270 | Tremble 271 | Victor 272 | Victors 273 | Villeneuve 274 | Vincent 275 | Vipond 276 | Voclain 277 | Yount 278 | -------------------------------------------------------------------------------- /data/names/German.txt: -------------------------------------------------------------------------------- 1 | Abbing 2 | Abel 3 | Abeln 4 | Abt 5 | Achilles 6 | Achterberg 7 | Acker 8 | Ackermann 9 | Adam 10 | Adenauer 11 | Adler 12 | Adlersflügel 13 | Aeschelman 14 | Albert 15 | Albrecht 16 | Aleshire 17 | Aleshite 18 | Althaus 19 | Amsel 20 | Andres 21 | Armbrüster 22 | Armbruster 23 | Artz 24 | Aue 25 | Auer 26 | Augustin 27 | Aust 28 | Autenburg 29 | Auttenberg 30 | Baasch 31 | Bach 32 | Bachmeier 33 | Bäcker 34 | Bader 35 | Bähr 36 | Bambach 37 | Bauer 38 | Bauers 39 | Baum 40 | Baumann 41 | Baumbach 42 | Baumgärtner 43 | Baumgartner 44 | Baumhauer 45 | Bayer 46 | Beck 47 | Becke 48 | Beckenbauer 49 | Becker 50 | Beckert 51 | Behrend 52 | Behrends 53 | Beitel 54 | Beltz 55 | Benn 56 | Berg 57 | Berger 58 | Bergfalk 59 | Beringer 60 | Bernat 61 | Best 62 | Beutel 63 | Beyer 64 | Beyersdorf 65 | Bieber 66 | Biermann 67 | Bischoffs 68 | Blau 69 | Blecher 70 | Bleier 71 | Blumenthal 72 | Blumstein 73 | Bocker 74 | Boehler 75 | Boer 76 | Boesch 77 | Böhler 78 | Böhm 79 | Böhme 80 | Böhmer 81 | Bohn 82 | Borchard 83 | Bösch 84 | Bosch 85 | Böttcher 86 | Brahms 87 | Brand 88 | Brandt 89 | Brant 90 | Brauer 91 | Braun 92 | Braune 93 | Breiner 94 | Breisacher 95 | Breitbarth 96 | Bretz 97 | Brinkerhoff 98 | Brodbeck 99 | Brose 100 | Brotz 101 | Bruhn 102 | Brun 103 | Brune 104 | Buchholz 105 | Buckholtz 106 | Buhr 107 | Bumgarner 108 | Burgstaller 109 | Busch 110 | Carver 111 | Chevrolet 112 | Cline 113 | Dahl 114 | Denzel 115 | Derrick 116 | Diefenbach 117 | Dieter 118 | Dietrich 119 | Dirchs 120 | Dittmar 121 | Dohman 122 | Drechsler 123 | Dreher 124 | Dreschner 125 | Dresdner 126 | Dressler 127 | Duerr 128 | Dunkle 129 | Dunst 130 | Dürr 131 | Eberhardt 132 | Ebner 133 | Ebner 134 | Eckstein 135 | Egger 136 | Eichel 137 | Eilerts 138 | Engel 139 | Enns 140 | Esser 141 | Essert 142 | Everhart 143 | Fabel 144 | Faerber 145 | Falk 146 | Falkenrath 147 | Färber 148 | Fashingbauer 149 | Faust 150 | Feigenbaum 151 | Feld 152 | Feldt 153 | Fenstermacher 154 | Fertig 155 | Fiedler 156 | Fischer 157 | Flater 158 | Fleischer 159 | Foerstner 160 | Forst 161 | Förstner 162 | Foth 163 | Frank 164 | Franke 165 | Frei 166 | Freud 167 | Freudenberger 168 | Freund 169 | Fried 170 | Friedrich 171 | Fromm 172 | Frost 173 | Fuchs 174 | Fuhrmann 175 | Fürst 176 | Fux 177 | Gabler 178 | Gaertner 179 | Garb 180 | Garber 181 | Gärtner 182 | Garver 183 | Gass 184 | Gehrig 185 | Gehring 186 | Geier 187 | Geiger 188 | Geisler 189 | Geissler 190 | Geiszler 191 | Gensch 192 | Gerber 193 | Gerhard 194 | Gerhardt 195 | Gerig 196 | Gerst 197 | Gerstle 198 | Gerver 199 | Giehl 200 | Giese 201 | Glöckner 202 | Goebel 203 | Goldschmidt 204 | Gorman 205 | Gott 206 | Gotti 207 | Gottlieb 208 | Gottschalk 209 | Graner 210 | Greenberg 211 | Groos 212 | Gros 213 | Gross 214 | Groß 215 | Große 216 | Grosse 217 | Größel 218 | Großel 219 | Großer 220 | Grosser 221 | Grosz 222 | Grünewald 223 | Günther 224 | Gunther 225 | Gutermuth 226 | Gwerder 227 | Haas 228 | Haase 229 | Haber 230 | Habich 231 | Habicht 232 | Hafner 233 | Hahn 234 | Hall 235 | Halle 236 | Harman 237 | Hartmann 238 | Hase 239 | Hasek 240 | Hasenkamp 241 | Hass 242 | Hauer 243 | Haupt 244 | Hausler 245 | Havener 246 | Heidrich 247 | Heinrich 248 | Heinrichs 249 | Heintze 250 | Hellewege 251 | Heppenheimer 252 | Herbert 253 | Hermann 254 | Herrmann 255 | Herschel 256 | Hertz 257 | Hildebrand 258 | Hinrichs 259 | Hintzen 260 | Hirsch 261 | Hoch 262 | Hochberg 263 | Hoefler 264 | Hofer 265 | Hoffman 266 | Hoffmann 267 | Höfler 268 | Hofmann 269 | Hofmeister 270 | Holst 271 | Holtzer 272 | Hölzer 273 | Holzer 274 | Holzknecht 275 | Holzmann 276 | Hoover 277 | Horn 278 | Horn 279 | Horowitz 280 | Houk 281 | Hüber 282 | Huber 283 | Huff 284 | Huffman 285 | Huffmann 286 | Hummel 287 | Hummel 288 | Hutmacher 289 | Ingersleben 290 | Jaeger 291 | Jäger 292 | Jager 293 | Jans 294 | Janson 295 | Janz 296 | Jollenbeck 297 | Jordan 298 | Jund 299 | Jung 300 | Junge 301 | Kahler 302 | Kaiser 303 | Kalb 304 | Kalbfleisch 305 | Kappel 306 | Karl 307 | Kaspar 308 | Kassmeyer 309 | Kästner 310 | Katz 311 | Kaube 312 | Käufer 313 | Kaufer 314 | Kauffmann 315 | Kaufman 316 | Keil 317 | Keller 318 | Kempf 319 | Kerner 320 | Kerper 321 | Kerwar 322 | Kerwer 323 | Kiefer 324 | Kiefer 325 | Kirchner 326 | Kistler 327 | Kistner 328 | Kleid 329 | Klein 330 | Klossner 331 | Knef 332 | Kneib 333 | Kneller 334 | Knepp 335 | Knochenmus 336 | Knopf 337 | Knopp 338 | Koch 339 | Kock 340 | Koenig 341 | Koenigsmann 342 | Köhl 343 | Kohl 344 | Köhler 345 | Kohler 346 | Kolbe 347 | König 348 | Königsmann 349 | Kopp 350 | Kraemer 351 | Krämer 352 | Kramer 353 | Krantz 354 | Kranz 355 | Kraus 356 | Krause 357 | Krauss 358 | Krauß 359 | Krebs 360 | Kröger 361 | Kron 362 | Kruckel 363 | Krüger 364 | Krüger 365 | Kruger 366 | Kruse 367 | Kruse 368 | Küchler 369 | Kuhn 370 | Kundert 371 | Kunkel 372 | Kunkle 373 | Kuntz 374 | Kunze 375 | Kurzmann 376 | Laberenz 377 | Lafrentz 378 | Lafrenz 379 | Landau 380 | Lang 381 | Lange 382 | Langenberg 383 | Langer 384 | Larenz 385 | Laurenz 386 | Lauritz 387 | Lawerenz 388 | Lawrenz 389 | Lehmann 390 | Lehrer 391 | Leitner 392 | Leitz 393 | Leitzke 394 | Lenz 395 | Leverenz 396 | Lewerentz 397 | Lewerenz 398 | Lichtenberg 399 | Lieberenz 400 | Linden 401 | Loewe 402 | Lohrenz 403 | Lorentz 404 | Lorenz 405 | Lorenzen 406 | Loris 407 | Loritz 408 | Löwe 409 | Ludwig 410 | Luther 411 | Maas 412 | Maier 413 | Mandel 414 | Mann 415 | Markwardt 416 | Marquardt 417 | Marquering 418 | Marquerink 419 | Martell 420 | Martin 421 | Martz 422 | Mas 423 | Maurer 424 | Maus 425 | Mayer 426 | Meier 427 | Mein 428 | Meindl 429 | Meinhardt 430 | Meisner 431 | Meissner 432 | Melsbach 433 | Mendel 434 | Mendelsohn 435 | Mendelssohn 436 | Messer 437 | Messerli 438 | Messmann 439 | Messner 440 | Metz 441 | Metz 442 | Metzger 443 | Meyer 444 | Michel 445 | Mohren 446 | Möller 447 | Morgenstern 448 | Moser 449 | Mueller 450 | Muhlfeld 451 | Müller 452 | Nagel 453 | Neuman 454 | Neumann 455 | Nuremberg 456 | Nussbaum 457 | Nussenbaum 458 | Oberst 459 | Oelberg 460 | Ohme 461 | Oliver 462 | Oppenheimer 463 | Ott 464 | Otto 465 | Oursler 466 | Pahlke 467 | Papke 468 | Papp 469 | Paternoster 470 | Paul 471 | Paulis 472 | Pawlitzki 473 | Penzig 474 | Peter 475 | Peters 476 | Pfaff 477 | Pfenning 478 | Plank 479 | Pletcher 480 | Porsche 481 | Portner 482 | Prinz 483 | Protz 484 | Rademacher 485 | Rademaker 486 | Rapp 487 | Raske 488 | Raskob 489 | Raskop 490 | Raskoph 491 | Regenbogen 492 | Reier 493 | Reiher 494 | Reiter 495 | Rettig 496 | Reuter 497 | Reuter 498 | Richard 499 | Richter 500 | Rier 501 | Riese 502 | Ritter 503 | Rose 504 | Rosenberg 505 | Rosenberger 506 | Rosenfeld 507 | Rot 508 | Roth 509 | Rothbauer 510 | Rothenberg 511 | Rothschild 512 | Sachs 513 | Saller 514 | Saller 515 | Salomon 516 | Salzwedel 517 | Samuel 518 | Sander 519 | Sauber 520 | Schäfer 521 | Scheer 522 | Scheinberg 523 | Schenck 524 | Schermer 525 | Schindler 526 | Schirmer 527 | Schlender 528 | Schlimme 529 | Schlusser 530 | Schmeling 531 | Schmid 532 | Schmidt 533 | Schmitt 534 | Schmitz 535 | Schneider 536 | Schnoor 537 | Schnur 538 | Schoettmer 539 | Schräder 540 | Schrader 541 | Schreck 542 | Schreier 543 | Schröder 544 | Schröder 545 | Schroeder 546 | Schroeter 547 | Schröter 548 | Schubert 549 | Schuchard 550 | Schuchardt 551 | Schuchert 552 | Schuhart 553 | Schuhmacher 554 | Schuler 555 | Schult 556 | Schulte 557 | Schultes 558 | Schultheis 559 | Schultheiss 560 | Schultheiß 561 | Schultz 562 | Schultze 563 | Schulz 564 | Schulze 565 | Schumacher 566 | Schuster 567 | Schuttmann 568 | Schwangau 569 | Schwartz 570 | Schwarz 571 | Schwarzenegger 572 | Schwenke 573 | Schwinghammer 574 | Seelenfreund 575 | Seidel 576 | Senft 577 | Senft 578 | Sheinfeld 579 | Shriver 580 | Siegel 581 | Siegel 582 | Siekert 583 | Siemon 584 | Silverstein 585 | Simen 586 | Simmon 587 | Simon 588 | Simons 589 | Siskin 590 | Siskind 591 | Sitz 592 | Sitz 593 | Slusser 594 | Solberg 595 | Sommer 596 | Sommer 597 | Sommer 598 | Sommer 599 | Sonnen 600 | Sorg 601 | Sorge 602 | Spannagel 603 | Specht 604 | Spellmeyer 605 | Spitznogle 606 | Sponaugle 607 | Stark 608 | Stauss 609 | Steen 610 | Steffen 611 | Stein 612 | Steinmann 613 | Stenger 614 | Sternberg 615 | Steube 616 | Steuben 617 | Stieber 618 | Stoppelbein 619 | Stoppelbein 620 | Strand 621 | Straub 622 | Strobel 623 | Strohkirch 624 | Stroman 625 | Stuber 626 | Stueck 627 | Stumpf 628 | Sturm 629 | Suess 630 | Sulzbach 631 | Swango 632 | Switzer 633 | Tangeman 634 | Tanzer 635 | Teufel 636 | Tiedeman 637 | Tifft 638 | Tillens 639 | Tobias 640 | Tolkien 641 | Tresler 642 | Tritten 643 | Trumbauer 644 | Tschida 645 | Unkle 646 | Unruh 647 | Unterbrink 648 | Ursler 649 | Vann 650 | Van tonder 651 | Vieth 652 | Vogel 653 | Vogt 654 | Vogts 655 | Voigt 656 | Voigts 657 | Volk 658 | Voll 659 | Von brandt 660 | Von essen 661 | Von grimmelshausen 662 | Von ingersleben 663 | Vonnegut 664 | Von wegberg 665 | Voss 666 | Voß 667 | Wägner 668 | Wagner 669 | Wähner 670 | Wahner 671 | Waldfogel 672 | Waldvogel 673 | Walkenhorst 674 | Walter 675 | Walther 676 | Waltz 677 | Wang 678 | Warner 679 | Waxweiler 680 | Weber 681 | Wechsler 682 | Wedekind 683 | Weeber 684 | Wegener 685 | Wegner 686 | Wehner 687 | Wehunt 688 | Weigand 689 | Weiman 690 | Weiner 691 | Weiss 692 | Weiß 693 | Welter 694 | Wendel 695 | Wendell 696 | Werner 697 | Wernher 698 | West 699 | Westerberg 700 | Wetterman 701 | Wetzel 702 | Wexler 703 | Wieck 704 | Wiegand 705 | Wildgrube 706 | Winter 707 | Winther 708 | Winther 709 | Wirner 710 | Wirnhier 711 | Wirt 712 | Wirth 713 | Wolf 714 | Wolff 715 | Wolter 716 | Wörner 717 | Wörnhör 718 | Wruck 719 | Wyman 720 | Xylander 721 | Zellweger 722 | Zilberschlag 723 | Zimmerman 724 | Zimmermann 725 | -------------------------------------------------------------------------------- /data/names/Greek.txt: -------------------------------------------------------------------------------- 1 | Adamidis 2 | Adamou 3 | Agelakos 4 | Akrivopoulos 5 | Alexandropoulos 6 | Anetakis 7 | Angelopoulos 8 | Antimisiaris 9 | Antipas 10 | Antonakos 11 | Antoniadis 12 | Antonopoulos 13 | Antonopoulos 14 | Antonopoulos 15 | Arvanitoyannis 16 | Avgerinos 17 | Banos 18 | Batsakis 19 | Bekyros 20 | Belesis 21 | Bertsimas 22 | Bilias 23 | Blades 24 | Bouloukos 25 | Brisimitzakis 26 | Bursinos 27 | Calogerakis 28 | Calpis 29 | Chellos 30 | Christakos 31 | Christodoulou 32 | Christou 33 | Chrysanthopoulos 34 | Chrysanthopoulos 35 | Comino 36 | Close 37 | Close 38 | Close 39 | Close 40 | Close 41 | Close 42 | Close 43 | Close 44 | Dalianis 45 | Danas 46 | Dasios 47 | Demakis 48 | Demarchis 49 | Demas 50 | Demetrious 51 | Dertilis 52 | Diakogeorgiou 53 | Dioletis 54 | Dounias 55 | Dritsas 56 | Drivakis 57 | Eatros 58 | Egonidis 59 | Eliopoulos 60 | Forakis 61 | Fotopoulos 62 | Fourakis 63 | Frangopoulos 64 | Galanopoulos 65 | Garofalis 66 | Gavril 67 | Gavrilopoulos 68 | Georgeakopoulos 69 | Geracimos 70 | Gianakopulos 71 | Giannakopoulos 72 | Giannakos 73 | Glynatsis 74 | Gomatos 75 | Grammatakakis 76 | Gravari 77 | Hadjiyianakies 78 | Hagias 79 | Haritopoulos 80 | Honjas 81 | Horiatis 82 | Houlis 83 | Jamussa 84 | Kaglantge 85 | Kalakos 86 | Kalogeria 87 | Kaloxylos 88 | Kanavos 89 | Kapsimalles 90 | Karahalios 91 | Karameros 92 | Karkampasis 93 | Karnoupakis 94 | Katsourinis 95 | Kefalas 96 | Kokkali 97 | Kokoris 98 | Kolovos 99 | Konstantatos 100 | Kosmas 101 | Kotsilimbas 102 | Kotsiopoulos 103 | Kouches 104 | Koulaxizis 105 | Koumanidis 106 | Kourempes 107 | Kouretas 108 | Kouropoulos 109 | Kouros 110 | Koustoubos 111 | Koutsoubos 112 | Kreskas 113 | Kringos 114 | Kyritsis 115 | Laganas 116 | Leontarakis 117 | Letsos 118 | Liatos 119 | Lillis 120 | Lolos 121 | Louverdis 122 | Makricosta 123 | Malihoudis 124 | Maneates 125 | Manos 126 | Manoukarakis 127 | Matsoukis 128 | Mentis 129 | Mersinias 130 | Metrofanis 131 | Michalaras 132 | Milionis 133 | Missiakos 134 | Moraitopoulos 135 | Nikolaou 136 | Nomikos 137 | Paitakes 138 | Paloumbas 139 | Panayiotopoulos 140 | Panoulias 141 | Pantelakos 142 | Pantelas 143 | Papadelias 144 | Papadopulos 145 | Papageorge 146 | Papoutsis 147 | Pappayiorgas 148 | Paraskevopoulos 149 | Paraskos 150 | Paschalis 151 | Patrianakos 152 | Patselas 153 | Pefanis 154 | Petimezas 155 | Petrakis 156 | Pezos 157 | Phocas 158 | Pispinis 159 | Polites 160 | Polymenakou 161 | Poniros 162 | Protopsaltis 163 | Rallis 164 | Rigatos 165 | Rorris 166 | Rousses 167 | Ruvelas 168 | Sakelaris 169 | Sakellariou 170 | Samios 171 | Sardelis 172 | Sfakianos 173 | Sklavenitis 174 | Sortras 175 | Sotiris 176 | Spyridis 177 | Stamatas 178 | Stamatelos 179 | Stavropoulos 180 | Strilakos 181 | Stroggylis 182 | Tableriou 183 | Taflambas 184 | Tassioglou 185 | Telis 186 | Tsoumada 187 | Theofilopoulos 188 | Theohari 189 | Totolos 190 | Tourna 191 | Tsahalis 192 | Tsangaris 193 | Tselios 194 | Tsogas 195 | Vamvakidis 196 | Varvitsiotes 197 | Vassilikos 198 | Vassilopulos 199 | Vlahos 200 | Vourlis 201 | Xydis 202 | Zaloumi 203 | Zouvelekis 204 | -------------------------------------------------------------------------------- /data/names/Irish.txt: -------------------------------------------------------------------------------- 1 | Adam 2 | Ahearn 3 | Aodh 4 | Aodha 5 | Aonghuis 6 | Aonghus 7 | Bhrighde 8 | Bradach 9 | Bradan 10 | Braden 11 | Brady 12 | Bran 13 | Brannon 14 | Brian 15 | Callaghan 16 | Caomh 17 | Carey 18 | Casey 19 | Cassidy 20 | Cathain 21 | Cathan 22 | Cathasach 23 | Ceallach 24 | Ceallachan 25 | Cearbhall 26 | Cennetig 27 | Ciardha 28 | Clark 29 | Cleirich 30 | Cleirigh 31 | Cnaimhin 32 | Coghlan 33 | Coilean 34 | Collins 35 | Colman 36 | Conall 37 | Conchobhar 38 | Conn 39 | Connell 40 | Connolly 41 | Cormac 42 | Corraidhin 43 | Cuidightheach 44 | Curran 45 | Dúbhshlaine 46 | Dalach 47 | Daly 48 | Damhain 49 | Damhan 50 | Delaney 51 | Desmond 52 | Devin 53 | Diarmaid 54 | Doherty 55 | Domhnall 56 | Donnchadh 57 | Donndubhan 58 | Donnell 59 | Donoghue 60 | Donovan 61 | Doyle 62 | Dubhain 63 | Dubhan 64 | Duncan 65 | Eoghan 66 | Eoin 67 | Eoin 68 | Faolan 69 | Farrell 70 | Fearghal 71 | Fergus 72 | Finn 73 | Finnegan 74 | Fionn 75 | Flanagan 76 | Flann 77 | Flynn 78 | Gallchobhar 79 | Gerald 80 | Giolla 81 | Gorman 82 | Hayden 83 | Ivor 84 | John 85 | Kavanagh 86 | Keefe 87 | Kelly 88 | Kennedy 89 | Lennon 90 | Login 91 | Macclelland 92 | Macdermott 93 | Maceachthighearna 94 | Macfarland 95 | Macghabhann 96 | Maciomhair 97 | Macshuibhne 98 | Madaidhin 99 | Madden 100 | Maguire 101 | Mahoney 102 | Maille 103 | Malone 104 | Manus 105 | Maolmhuaidh 106 | Mathghamhain 107 | Maurice 108 | Mcguire 109 | Mckay 110 | Mclain 111 | Mcmahon 112 | Mcnab 113 | Mcneil 114 | Meadhra 115 | Michael 116 | Milligan 117 | Mochan 118 | Mohan 119 | Molloy 120 | Monahan 121 | Mooney 122 | Muirchertach 123 | Mullen 124 | Mulryan 125 | Murchadh 126 | Murphy 127 | Names 128 | Naoimhin 129 | Naomhan 130 | Neil 131 | Neville 132 | Nevin 133 | Niadh 134 | Niall 135 | Nolan 136 | Nuallan 137 | O'Boyle 138 | O'Brien 139 | O'Byrne 140 | O'Donnell 141 | O'Hannagain 142 | O'Hannigain 143 | O'Keefe 144 | O'Mooney 145 | O'Neal 146 | O'Boyle 147 | O'Bree 148 | O'Brian 149 | O'Brien 150 | O'Callaghann 151 | O'Connell 152 | O'Connor 153 | O'Dell 154 | O'Doherty 155 | O'Donnell 156 | O'Donoghue 157 | O'Dowd 158 | O'Driscoll 159 | O'Gorman 160 | O'Grady 161 | O'Hagan 162 | O'Halloran 163 | O'Hanlon 164 | O'Hara 165 | O'Hare 166 | O'Kane 167 | O'Keefe 168 | O'Keeffe 169 | O'Kelly 170 | O'Leary 171 | O'Loughlin 172 | O'Mahoney 173 | O'Mahony 174 | O'Malley 175 | O'Meara 176 | O'Neal 177 | O'Neill 178 | O'Reilly 179 | O'Rourke 180 | O'Ryan 181 | O'Shea 182 | O'Sullivan 183 | O'Toole 184 | Patrick 185 | Peatain 186 | Pharlain 187 | Power 188 | Quigley 189 | Quinn 190 | Quirke 191 | Raghailligh 192 | Reagan 193 | Register 194 | Reilly 195 | Reynold 196 | Rhys 197 | Riagain 198 | Riagan 199 | Riain 200 | Rian 201 | Rinn 202 | Roach 203 | Rodagh 204 | Rory 205 | Ruadh 206 | Ruadhain 207 | Ruadhan 208 | Ruaidh 209 | Samuel 210 | Scolaidhe 211 | Seaghdha 212 | Sechnall 213 | Seighin 214 | Shannon 215 | Sheehy 216 | Simon 217 | Sioda 218 | Sloan 219 | Sluaghadhan 220 | Suaird 221 | Sullivan 222 | Tadhg 223 | Tadhgan 224 | Taidhg 225 | Teagan 226 | Teague 227 | Tighearnach 228 | Tracey 229 | Treasach 230 | Whalen 231 | Whelan 232 | William 233 | -------------------------------------------------------------------------------- /data/names/Italian.txt: -------------------------------------------------------------------------------- 1 | Abandonato 2 | Abatangelo 3 | Abatantuono 4 | Abate 5 | Abategiovanni 6 | Abatescianni 7 | Abbà 8 | Abbadelli 9 | Abbascia 10 | Abbatangelo 11 | Abbatantuono 12 | Abbate 13 | Abbatelli 14 | Abbaticchio 15 | Abbiati 16 | Abbracciabene 17 | Abbracciabeni 18 | Abelli 19 | Abelló 20 | Abrami 21 | Abramo 22 | Acardi 23 | Accardi 24 | Accardo 25 | Acciai 26 | Acciaio 27 | Acciaioli 28 | Acconci 29 | Acconcio 30 | Accorsi 31 | Accorso 32 | Accosi 33 | Accursio 34 | Acerbi 35 | Acone 36 | Aconi 37 | Acqua 38 | Acquafredda 39 | Acquarone 40 | Acquati 41 | Adalardi 42 | Adami 43 | Adamo 44 | Adamoli 45 | Addario 46 | Adelardi 47 | Adessi 48 | Adimari 49 | Adriatico 50 | Affini 51 | Africani 52 | Africano 53 | Agani 54 | Aggi 55 | Aggio 56 | Agli 57 | Agnelli 58 | Agnellutti 59 | Agnusdei 60 | Agosti 61 | Agostini 62 | Agresta 63 | Agrioli 64 | Aiello 65 | Aiolfi 66 | Airaldi 67 | Airò 68 | Aita 69 | Ajello 70 | Alagona 71 | Alamanni 72 | Albanesi 73 | Albani 74 | Albano 75 | Alberghi 76 | Alberghini 77 | Alberici 78 | Alberighi 79 | Albero 80 | Albini 81 | Albricci 82 | Albrici 83 | Alcheri 84 | Aldebrandi 85 | Alderisi 86 | Alduino 87 | Alemagna 88 | Aleppo 89 | Alesci 90 | Alescio 91 | Alesi 92 | Alesini 93 | Alesio 94 | Alessandri 95 | Alessi 96 | Alfero 97 | Aliberti 98 | Alinari 99 | Aliprandi 100 | Allegri 101 | Allegro 102 | Alò 103 | Aloia 104 | Aloisi 105 | Altamura 106 | Altimari 107 | Altoviti 108 | Alunni 109 | Amadei 110 | Amadori 111 | Amalberti 112 | Amantea 113 | Amato 114 | Amatore 115 | Ambrogi 116 | Ambrosi 117 | Amello 118 | Amerighi 119 | Amoretto 120 | Angioli 121 | Ansaldi 122 | Anselmetti 123 | Anselmi 124 | Antonelli 125 | Antonini 126 | Antonino 127 | Aquila 128 | Aquino 129 | Arbore 130 | Ardiccioni 131 | Ardizzone 132 | Ardovini 133 | Arena 134 | Aringheri 135 | Arlotti 136 | Armani 137 | Armati 138 | Armonni 139 | Arnolfi 140 | Arnoni 141 | Arrighetti 142 | Arrighi 143 | Arrigucci 144 | Aucciello 145 | Azzarà 146 | Baggi 147 | Baggio 148 | Baglio 149 | Bagni 150 | Bagnoli 151 | Balboni 152 | Baldi 153 | Baldini 154 | Baldinotti 155 | Baldovini 156 | Bandini 157 | Bandoni 158 | Barbieri 159 | Barone 160 | Barsetti 161 | Bartalotti 162 | Bartolomei 163 | Bartolomeo 164 | Barzetti 165 | Basile 166 | Bassanelli 167 | Bassani 168 | Bassi 169 | Basso 170 | Basurto 171 | Battaglia 172 | Bazzoli 173 | Bellandi 174 | Bellandini 175 | Bellincioni 176 | Bellini 177 | Bello 178 | Bellomi 179 | Belloni 180 | Belluomi 181 | Belmonte 182 | Bencivenni 183 | Benedetti 184 | Benenati 185 | Benetton 186 | Benini 187 | Benivieni 188 | Benvenuti 189 | Berardi 190 | Bergamaschi 191 | Berti 192 | Bertolini 193 | Biancardi 194 | Bianchi 195 | Bicchieri 196 | Biondi 197 | Biondo 198 | Boerio 199 | Bologna 200 | Bondesan 201 | Bonomo 202 | Borghi 203 | Borgnino 204 | Borgogni 205 | Bosco 206 | Bove 207 | Bovér 208 | Boveri 209 | Brambani 210 | Brambilla 211 | Breda 212 | Brioschi 213 | Brivio 214 | Brunetti 215 | Bruno 216 | Buffone 217 | Bulgarelli 218 | Bulgari 219 | Buonarroti 220 | Busto 221 | Caiazzo 222 | Caito 223 | Caivano 224 | Calabrese 225 | Calligaris 226 | Campana 227 | Campo 228 | Cantu 229 | Capello 230 | Capello 231 | Capello 232 | Capitani 233 | Carbone 234 | Carboni 235 | Carideo 236 | Carlevaro 237 | Caro 238 | Carracci 239 | Carrara 240 | Caruso 241 | Cassano 242 | Castro 243 | Catalano 244 | Cattaneo 245 | Cavalcante 246 | Cavallo 247 | Cingolani 248 | Cino 249 | Cipriani 250 | Cisternino 251 | Coiro 252 | Cola 253 | Colombera 254 | Colombo 255 | Columbo 256 | Como 257 | Como 258 | Confortola 259 | Conti 260 | Corna 261 | Corti 262 | Corvi 263 | Costa 264 | Costantini 265 | Costanzo 266 | Cracchiolo 267 | Cremaschi 268 | Cremona 269 | Cremonesi 270 | Crespo 271 | Croce 272 | Crocetti 273 | Cucinotta 274 | Cuocco 275 | Cuoco 276 | D'ambrosio 277 | Damiani 278 | D'amore 279 | D'angelo 280 | D'antonio 281 | De angelis 282 | De campo 283 | De felice 284 | De filippis 285 | De fiore 286 | De laurentis 287 | De luca 288 | De palma 289 | De rege 290 | De santis 291 | De vitis 292 | Di antonio 293 | Di caprio 294 | Di mercurio 295 | Dinapoli 296 | Dioli 297 | Di pasqua 298 | Di pietro 299 | Di stefano 300 | Donati 301 | D'onofrio 302 | Drago 303 | Durante 304 | Elena 305 | Episcopo 306 | Ermacora 307 | Esposito 308 | Evangelista 309 | Fabbri 310 | Fabbro 311 | Falco 312 | Faraldo 313 | Farina 314 | Farro 315 | Fattore 316 | Fausti 317 | Fava 318 | Favero 319 | Fermi 320 | Ferrara 321 | Ferrari 322 | Ferraro 323 | Ferrero 324 | Ferro 325 | Fierro 326 | Filippi 327 | Fini 328 | Fiore 329 | Fiscella 330 | Fiscella 331 | Fonda 332 | Fontana 333 | Fortunato 334 | Franco 335 | Franzese 336 | Furlan 337 | Gabrielli 338 | Gagliardi 339 | Gallo 340 | Ganza 341 | Garfagnini 342 | Garofalo 343 | Gaspari 344 | Gatti 345 | Genovese 346 | Gentile 347 | Germano 348 | Giannino 349 | Gimondi 350 | Giordano 351 | Gismondi 352 | Giùgovaz 353 | Giunta 354 | Goretti 355 | Gori 356 | Greco 357 | Grillo 358 | Grimaldi 359 | Gronchi 360 | Guarneri 361 | Guerra 362 | Guerriero 363 | Guidi 364 | Guttuso 365 | Idoni 366 | Innocenti 367 | Labriola 368 | Làconi 369 | Laganà 370 | Lagomarsìno 371 | Lagorio 372 | Laguardia 373 | Lama 374 | Lamberti 375 | Lamon 376 | Landi 377 | Lando 378 | Landolfi 379 | Laterza 380 | Laurito 381 | Lazzari 382 | Lecce 383 | Leccese 384 | Leggièri 385 | Lèmmi 386 | Leone 387 | Leoni 388 | Lippi 389 | Locatelli 390 | Lombardi 391 | Longo 392 | Lupo 393 | Luzzatto 394 | Maestri 395 | Magro 396 | Mancini 397 | Manco 398 | Mancuso 399 | Manfredi 400 | Manfredonia 401 | Mantovani 402 | Marchegiano 403 | Marchesi 404 | Marchetti 405 | Marchioni 406 | Marconi 407 | Mari 408 | Maria 409 | Mariani 410 | Marino 411 | Marmo 412 | Martelli 413 | Martinelli 414 | Masi 415 | Masin 416 | Mazza 417 | Merlo 418 | Messana 419 | Micheli 420 | Milani 421 | Milano 422 | Modugno 423 | Mondadori 424 | Mondo 425 | Montagna 426 | Montana 427 | Montanari 428 | Monte 429 | Monti 430 | Morandi 431 | Morello 432 | Moretti 433 | Morra 434 | Moschella 435 | Mosconi 436 | Motta 437 | Muggia 438 | Muraro 439 | Murgia 440 | Murtas 441 | Nacar 442 | Naggi 443 | Naggia 444 | Naldi 445 | Nana 446 | Nani 447 | Nanni 448 | Nannini 449 | Napoleoni 450 | Napoletani 451 | Napoliello 452 | Nardi 453 | Nardo 454 | Nardovino 455 | Nasato 456 | Nascimbene 457 | Nascimbeni 458 | Natale 459 | Nave 460 | Nazario 461 | Necchi 462 | Negri 463 | Negrini 464 | Nelli 465 | Nenci 466 | Nepi 467 | Neri 468 | Neroni 469 | Nervetti 470 | Nervi 471 | Nespola 472 | Nicastro 473 | Nicchi 474 | Nicodemo 475 | Nicolai 476 | Nicolosi 477 | Nicosia 478 | Nicotera 479 | Nieddu 480 | Nieri 481 | Nigro 482 | Nisi 483 | Nizzola 484 | Noschese 485 | Notaro 486 | Notoriano 487 | Oberti 488 | Oberto 489 | Ongaro 490 | Orlando 491 | Orsini 492 | Pace 493 | Padovan 494 | Padovano 495 | Pagani 496 | Pagano 497 | Palladino 498 | Palmisano 499 | Palumbo 500 | Panzavecchia 501 | Parisi 502 | Parma 503 | Parodi 504 | Parri 505 | Parrino 506 | Passerini 507 | Pastore 508 | Paternoster 509 | Pavesi 510 | Pavone 511 | Pavoni 512 | Pecora 513 | Pedrotti 514 | Pellegrino 515 | Perugia 516 | Pesaresi 517 | Pesaro 518 | Pesce 519 | Petri 520 | Pherigo 521 | Piazza 522 | Piccirillo 523 | Piccoli 524 | Pierno 525 | Pietri 526 | Pini 527 | Piovene 528 | Piraino 529 | Pisani 530 | Pittaluga 531 | Poggi 532 | Poggio 533 | Poletti 534 | Pontecorvo 535 | Portelli 536 | Porto 537 | Portoghese 538 | Potenza 539 | Pozzi 540 | Profeta 541 | Prosdocimi 542 | Provenza 543 | Provenzano 544 | Pugliese 545 | Quaranta 546 | Quattrocchi 547 | Ragno 548 | Raimondi 549 | Rais 550 | Rana 551 | Raneri 552 | Rao 553 | Rapallino 554 | Ratti 555 | Ravenna 556 | Ré 557 | Ricchetti 558 | Ricci 559 | Riggi 560 | Righi 561 | Rinaldi 562 | Riva 563 | Rizzo 564 | Robustelli 565 | Rocca 566 | Rocchi 567 | Rocco 568 | Roma 569 | Roma 570 | Romagna 571 | Romagnoli 572 | Romano 573 | Romano 574 | Romero 575 | Roncalli 576 | Ronchi 577 | Rosa 578 | Rossi 579 | Rossini 580 | Rotolo 581 | Rovigatti 582 | Ruggeri 583 | Russo 584 | Rustici 585 | Ruzzier 586 | Sabbadin 587 | Sacco 588 | Sala 589 | Salomon 590 | Salucci 591 | Salvaggi 592 | Salvai 593 | Salvail 594 | Salvatici 595 | Salvay 596 | Sanna 597 | Sansone 598 | Santini 599 | Santoro 600 | Sapienti 601 | Sarno 602 | Sarti 603 | Sartini 604 | Sarto 605 | Savona 606 | Scarpa 607 | Scarsi 608 | Scavo 609 | Sciacca 610 | Sciacchitano 611 | Sciarra 612 | Scordato 613 | Scotti 614 | Scutese 615 | Sebastiani 616 | Sebastino 617 | Segreti 618 | Selmone 619 | Selvaggio 620 | Serafin 621 | Serafini 622 | Serpico 623 | Sessa 624 | Sgro 625 | Siena 626 | Silvestri 627 | Sinagra 628 | Sinagra 629 | Soldati 630 | Somma 631 | Sordi 632 | Soriano 633 | Sorrentino 634 | Spada 635 | Spanò 636 | Sparacello 637 | Speziale 638 | Spini 639 | Stabile 640 | Stablum 641 | Stilo 642 | Sultana 643 | Tafani 644 | Tamàro 645 | Tamboia 646 | Tanzi 647 | Tarantino 648 | Taverna 649 | Tedesco 650 | Terranova 651 | Terzi 652 | Tessaro 653 | Testa 654 | Tiraboschi 655 | Tivoli 656 | Todaro 657 | Toloni 658 | Tornincasa 659 | Toselli 660 | Tosetti 661 | Tosi 662 | Tosto 663 | Trapani 664 | Traversa 665 | Traversi 666 | Traversini 667 | Traverso 668 | Trucco 669 | Trudu 670 | Tumicelli 671 | Turati 672 | Turchi 673 | Uberti 674 | Uccello 675 | Uggeri 676 | Ughi 677 | Ungaretti 678 | Ungaro 679 | Vacca 680 | Vaccaro 681 | Valenti 682 | Valentini 683 | Valerio 684 | Varano 685 | Ventimiglia 686 | Ventura 687 | Verona 688 | Veronesi 689 | Vescovi 690 | Vespa 691 | Vestri 692 | Vicario 693 | Vico 694 | Vigo 695 | Villa 696 | Vinci 697 | Vinci 698 | Viola 699 | Vitali 700 | Viteri 701 | Voltolini 702 | Zambrano 703 | Zanetti 704 | Zangari 705 | Zappa 706 | Zeni 707 | Zini 708 | Zino 709 | Zunino 710 | -------------------------------------------------------------------------------- /data/names/Japanese.txt: -------------------------------------------------------------------------------- 1 | Abe 2 | Abukara 3 | Adachi 4 | Aida 5 | Aihara 6 | Aizawa 7 | Ajibana 8 | Akaike 9 | Akamatsu 10 | Akatsuka 11 | Akechi 12 | Akera 13 | Akimoto 14 | Akita 15 | Akiyama 16 | Akutagawa 17 | Amagawa 18 | Amaya 19 | Amori 20 | Anami 21 | Ando 22 | Anzai 23 | Aoki 24 | Arai 25 | Arakawa 26 | Araki 27 | Arakida 28 | Arato 29 | Arihyoshi 30 | Arishima 31 | Arita 32 | Ariwa 33 | Ariwara 34 | Asahara 35 | Asahi 36 | Asai 37 | Asano 38 | Asanuma 39 | Asari 40 | Ashia 41 | Ashida 42 | Ashikaga 43 | Asuhara 44 | Atshushi 45 | Ayabito 46 | Ayugai 47 | Baba 48 | Baisotei 49 | Bando 50 | Bunya 51 | Chiba 52 | Chikamatsu 53 | Chikanatsu 54 | Chino 55 | Chishu 56 | Choshi 57 | Daishi 58 | Dan 59 | Date 60 | Dazai 61 | Deguchi 62 | Deushi 63 | Doi 64 | Ebina 65 | Ebisawa 66 | Eda 67 | Egami 68 | Eguchi 69 | Ekiguchi 70 | Endo 71 | Endoso 72 | Enoki 73 | Enomoto 74 | Erizawa 75 | Eto 76 | Etsuko 77 | Ezakiya 78 | Fuchida 79 | Fugunaga 80 | Fujikage 81 | Fujimaki 82 | Fujimoto 83 | Fujioka 84 | Fujishima 85 | Fujita 86 | Fujiwara 87 | Fukao 88 | Fukayama 89 | Fukuda 90 | Fukumitsu 91 | Fukunaka 92 | Fukuoka 93 | Fukusaku 94 | Fukushima 95 | Fukuyama 96 | Fukuzawa 97 | Fumihiko 98 | Funabashi 99 | Funaki 100 | Funakoshi 101 | Furusawa 102 | Fuschida 103 | Fuse 104 | Futabatei 105 | Fuwa 106 | Gakusha 107 | Genda 108 | Genji 109 | Gensai 110 | Godo 111 | Goto 112 | Gushiken 113 | Hachirobei 114 | Haga 115 | Hagino 116 | Hagiwara 117 | Hama 118 | Hamacho 119 | Hamada 120 | Hamaguchi 121 | Hamamoto 122 | Hanabusa 123 | Hanari 124 | Handa 125 | Hara 126 | Harada 127 | Haruguchi 128 | Hasegawa 129 | Hasekura 130 | Hashimoto 131 | Hasimoto 132 | Hatakeda 133 | Hatakeyama 134 | Hatayama 135 | Hatoyama 136 | Hattori 137 | Hayakawa 138 | Hayami 139 | Hayashi 140 | Hayashida 141 | Hayata 142 | Hayuata 143 | Hida 144 | Hideaki 145 | Hideki 146 | Hideyoshi 147 | Higashikuni 148 | Higashiyama 149 | Higo 150 | Higoshi 151 | Higuchi 152 | Hike 153 | Hino 154 | Hira 155 | Hiraga 156 | Hiraki 157 | Hirano 158 | Hiranuma 159 | Hiraoka 160 | Hirase 161 | Hirasi 162 | Hirata 163 | Hiratasuka 164 | Hirayama 165 | Hiro 166 | Hirose 167 | Hirota 168 | Hiroyuki 169 | Hisamatsu 170 | Hishida 171 | Hishikawa 172 | Hitomi 173 | Hiyama 174 | Hohki 175 | Hojo 176 | Hokusai 177 | Honami 178 | Honda 179 | Hori 180 | Horigome 181 | Horigoshi 182 | Horiuchi 183 | Horri 184 | Hoshino 185 | Hosokawa 186 | Hosokaya 187 | Hotate 188 | Hotta 189 | Hyata 190 | Hyobanshi 191 | Ibi 192 | Ibu 193 | Ibuka 194 | Ichigawa 195 | Ichihara 196 | Ichikawa 197 | Ichimonji 198 | Ichiro 199 | Ichisada 200 | Ichiyusai 201 | Idane 202 | Iemochi 203 | Ienari 204 | Iesada 205 | Ieyasu 206 | Ieyoshi 207 | Igarashi 208 | Ihara 209 | Ii 210 | Iida 211 | Iijima 212 | Iitaka 213 | Ijichi 214 | Ijiri 215 | Ikeda 216 | Ikina 217 | Ikoma 218 | Imada 219 | Imagawa 220 | Imai 221 | Imaizumi 222 | Imamura 223 | Imoo 224 | Ina 225 | Inaba 226 | Inao 227 | Inihara 228 | Ino 229 | Inoguchi 230 | Inokuma 231 | Inoue 232 | Inouye 233 | Inukai 234 | Ippitsusai 235 | Irie 236 | Iriye 237 | Isayama 238 | Ise 239 | Iseki 240 | Iseya 241 | Ishibashi 242 | Ishida 243 | Ishiguro 244 | Ishihara 245 | Ishikawa 246 | Ishimaru 247 | Ishimura 248 | Ishinomori 249 | Ishiyama 250 | Isobe 251 | Isoda 252 | Isozaki 253 | Itagaki 254 | Itami 255 | Ito 256 | Itoh 257 | Iwahara 258 | Iwahashi 259 | Iwakura 260 | Iwasa 261 | Iwasaki 262 | Izumi 263 | Jimbo 264 | Jippensha 265 | Jo 266 | Joshuya 267 | Joshuyo 268 | Jukodo 269 | Jumonji 270 | Kada 271 | Kagabu 272 | Kagawa 273 | Kahae 274 | Kahaya 275 | Kaibara 276 | Kaima 277 | Kajahara 278 | Kajitani 279 | Kajiwara 280 | Kajiyama 281 | Kakinomoto 282 | Kakutama 283 | Kamachi 284 | Kamata 285 | Kaminaga 286 | Kamio 287 | Kamioka 288 | Kamisaka 289 | Kamo 290 | Kamon 291 | Kan 292 | Kanada 293 | Kanagaki 294 | Kanegawa 295 | Kaneko 296 | Kanesaka 297 | Kano 298 | Karamorita 299 | Karube 300 | Karubo 301 | Kasahara 302 | Kasai 303 | Kasamatsu 304 | Kasaya 305 | Kase 306 | Kashiwagi 307 | Kasuse 308 | Kataoka 309 | Katayama 310 | Katayanagi 311 | Kate 312 | Kato 313 | Katoaka 314 | Katsu 315 | Katsukawa 316 | Katsumata 317 | Katsura 318 | Katsushika 319 | Kawabata 320 | Kawachi 321 | Kawagichi 322 | Kawagishi 323 | Kawaguchi 324 | Kawai 325 | Kawaii 326 | Kawakami 327 | Kawamata 328 | Kawamura 329 | Kawasaki 330 | Kawasawa 331 | Kawashima 332 | Kawasie 333 | Kawatake 334 | Kawate 335 | Kawayama 336 | Kawazu 337 | Kaza 338 | Kazuyoshi 339 | Kenkyusha 340 | Kenmotsu 341 | Kentaro 342 | Ki 343 | Kido 344 | Kihara 345 | Kijimuta 346 | Kijmuta 347 | Kikkawa 348 | Kikuchi 349 | Kikugawa 350 | Kikui 351 | Kikutake 352 | Kimio 353 | Kimiyama 354 | Kimura 355 | Kinashita 356 | Kinoshita 357 | Kinugasa 358 | Kira 359 | Kishi 360 | Kiski 361 | Kita 362 | Kitabatake 363 | Kitagawa 364 | Kitamura 365 | Kitano 366 | Kitao 367 | Kitoaji 368 | Ko 369 | Kobayashi 370 | Kobi 371 | Kodama 372 | Koga 373 | Kogara 374 | Kogo 375 | Koguchi 376 | Koiso 377 | Koizumi 378 | Kojima 379 | Kokan 380 | Komagata 381 | Komatsu 382 | Komatsuzaki 383 | Komine 384 | Komiya 385 | Komon 386 | Komura 387 | Kon 388 | Konae 389 | Konda 390 | Kondo 391 | Konishi 392 | Kono 393 | Konoe 394 | Koruba 395 | Koshin 396 | Kotara 397 | Kotoku 398 | Koyama 399 | Koyanagi 400 | Kozu 401 | Kubo 402 | Kubota 403 | Kudara 404 | Kudo 405 | Kuga 406 | Kumagae 407 | Kumasaka 408 | Kunda 409 | Kunikida 410 | Kunisada 411 | Kuno 412 | Kunomasu 413 | Kuramochi 414 | Kuramoto 415 | Kurata 416 | Kurkawa 417 | Kurmochi 418 | Kuroda 419 | Kurofuji 420 | Kurogane 421 | Kurohiko 422 | Kuroki 423 | Kurosawa 424 | Kurusu 425 | Kusatsu 426 | Kusonoki 427 | Kusuhara 428 | Kusunoki 429 | Kuwabara 430 | Kwakami 431 | Kyubei 432 | Maeda 433 | Maehata 434 | Maeno 435 | Maita 436 | Makiguchi 437 | Makino 438 | Makioka 439 | Makuda 440 | Marubeni 441 | Marugo 442 | Marusa 443 | Maruya 444 | Maruyama 445 | Masanobu 446 | Masaoka 447 | Mashita 448 | Masoni 449 | Masudu 450 | Masuko 451 | Masuno 452 | Masuzoe 453 | Matano 454 | Matokai 455 | Matoke 456 | Matsuda 457 | Matsukata 458 | Matsuki 459 | Matsumara 460 | Matsumoto 461 | Matsumura 462 | Matsuo 463 | Matsuoka 464 | Matsura 465 | Matsushina 466 | Matsushita 467 | Matsuya 468 | Matsuzawa 469 | Mayuzumi 470 | Mazaki 471 | Mazawa 472 | Mazuka 473 | Mifune 474 | Mihashi 475 | Miki 476 | Mimasuya 477 | Minabuchi 478 | Minami 479 | Minamoto 480 | Minatoya 481 | Minobe 482 | Mishima 483 | Mitsubishi 484 | Mitsuharu 485 | Mitsui 486 | Mitsukuri 487 | Mitsuwa 488 | Mitsuya 489 | Mitzusaka 490 | Miura 491 | Miwa 492 | Miyagi 493 | Miyahara 494 | Miyajima 495 | Miyake 496 | Miyamae 497 | Miyamoto 498 | Miyazaki 499 | Miyazawa 500 | Miyoshi 501 | Mizoguchi 502 | Mizumaki 503 | Mizuno 504 | Mizutani 505 | Modegi 506 | Momotami 507 | Momotani 508 | Monomonoi 509 | Mori 510 | Moriguchi 511 | Morimoto 512 | Morinaga 513 | Morioka 514 | Morishita 515 | Morisue 516 | Morita 517 | Morri 518 | Moto 519 | Motoori 520 | Motoyoshi 521 | Munakata 522 | Munkata 523 | Muraguchi 524 | Murakami 525 | Muraoka 526 | Murasaki 527 | Murase 528 | Murata 529 | Murkami 530 | Muro 531 | Muruyama 532 | Mushanaokoji 533 | Mushashibo 534 | Muso 535 | Mutsu 536 | Nagahama 537 | Nagai 538 | Nagano 539 | Nagasawa 540 | Nagase 541 | Nagata 542 | Nagatsuka 543 | Nagumo 544 | Naito 545 | Nakada 546 | Nakadai 547 | Nakadan 548 | Nakae 549 | Nakagawa 550 | Nakahara 551 | Nakajima 552 | Nakamoto 553 | Nakamura 554 | Nakane 555 | Nakanishi 556 | Nakano 557 | Nakanoi 558 | Nakao 559 | Nakasato 560 | Nakasawa 561 | Nakasone 562 | Nakata 563 | Nakatoni 564 | Nakayama 565 | Nakazawa 566 | Namiki 567 | Nanami 568 | Narahashi 569 | Narato 570 | Narita 571 | Nataga 572 | Natsume 573 | Nawabe 574 | Nemoto 575 | Niijima 576 | Nijo 577 | Ninomiya 578 | Nishi 579 | Nishihara 580 | Nishikawa 581 | Nishimoto 582 | Nishimura 583 | Nishimuraya 584 | Nishio 585 | Nishiwaki 586 | Nitta 587 | Nobunaga 588 | Noda 589 | Nogi 590 | Noguchi 591 | Nogushi 592 | Nomura 593 | Nonomura 594 | Noro 595 | Nosaka 596 | Nose 597 | Nozaki 598 | Nozara 599 | Numajiri 600 | Numata 601 | Obata 602 | Obinata 603 | Obuchi 604 | Ochiai 605 | Ochida 606 | Odaka 607 | Ogata 608 | Ogiwara 609 | Ogura 610 | Ogyu 611 | Ohba 612 | Ohira 613 | Ohishi 614 | Ohka 615 | Ohmae 616 | Ohmiya 617 | Oichi 618 | Oinuma 619 | Oishi 620 | Okabe 621 | Okada 622 | Okakura 623 | Okamoto 624 | Okamura 625 | Okanao 626 | Okanaya 627 | Okano 628 | Okasawa 629 | Okawa 630 | Okazaki 631 | Okazawaya 632 | Okimasa 633 | Okimoto 634 | Okita 635 | Okubo 636 | Okuda 637 | Okui 638 | Okuma 639 | Okuma 640 | Okumura 641 | Okura 642 | Omori 643 | Omura 644 | Onishi 645 | Ono 646 | Onoda 647 | Onoe 648 | Onohara 649 | Ooka 650 | Osagawa 651 | Osaragi 652 | Oshima 653 | Oshin 654 | Ota 655 | Otaka 656 | Otake 657 | Otani 658 | Otomo 659 | Otsu 660 | Otsuka 661 | Ouchi 662 | Oyama 663 | Ozaki 664 | Ozawa 665 | Ozu 666 | Raikatuji 667 | Royama 668 | Ryusaki 669 | Sada 670 | Saeki 671 | Saga 672 | Saigo 673 | Saiki 674 | Saionji 675 | Saito 676 | Saitoh 677 | Saji 678 | Sakagami 679 | Sakai 680 | Sakakibara 681 | Sakamoto 682 | Sakanoue 683 | Sakata 684 | Sakiyurai 685 | Sakoda 686 | Sakubara 687 | Sakuraba 688 | Sakurai 689 | Sammiya 690 | Sanda 691 | Sanjo 692 | Sano 693 | Santo 694 | Saromi 695 | Sarumara 696 | Sasada 697 | Sasakawa 698 | Sasaki 699 | Sassa 700 | Satake 701 | Sato 702 | Satoh 703 | Satoya 704 | Sawamatsu 705 | Sawamura 706 | Sayuki 707 | Segawa 708 | Sekigawa 709 | Sekine 710 | Sekozawa 711 | Sen 712 | Senmatsu 713 | Seo 714 | Serizawa 715 | Shiba 716 | Shibaguchi 717 | Shibanuma 718 | Shibasaki 719 | Shibasawa 720 | Shibata 721 | Shibukji 722 | Shichirobei 723 | Shidehara 724 | Shiga 725 | Shiganori 726 | Shige 727 | Shigeki 728 | Shigemitsu 729 | Shigi 730 | Shikitei 731 | Shikuk 732 | Shima 733 | Shimada 734 | Shimakage 735 | Shimamura 736 | Shimanouchi 737 | Shimaoka 738 | Shimazaki 739 | Shimazu 740 | Shimedzu 741 | Shimizu 742 | Shimohira 743 | Shimon 744 | Shimura 745 | Shimuzu 746 | Shinko 747 | Shinozaki 748 | Shinozuka 749 | Shintaro 750 | Shiokawa 751 | Shiomi 752 | Shiomiya 753 | Shionoya 754 | Shiotani 755 | Shioya 756 | Shirahata 757 | Shirai 758 | Shiraishi 759 | Shirane 760 | Shirasu 761 | Shiratori 762 | Shirokawa 763 | Shiroyama 764 | Shiskikura 765 | Shizuma 766 | Shobo 767 | Shoda 768 | Shunji 769 | Shunsen 770 | Siagyo 771 | Soga 772 | Sohda 773 | Soho 774 | Soma 775 | Someya 776 | Sone 777 | Sonoda 778 | Soseki 779 | Sotomura 780 | Suenami 781 | Sugai 782 | Sugase 783 | Sugawara 784 | Sugihara 785 | Sugimura 786 | Sugisata 787 | Sugita 788 | Sugitani 789 | Sugiyama 790 | Sumitimo 791 | Sunada 792 | Suzambo 793 | Suzuki 794 | Tabuchi 795 | Tadeshi 796 | Tagawa 797 | Taguchi 798 | Taira 799 | Taka 800 | Takabe 801 | Takagaki 802 | Takagawa 803 | Takagi 804 | Takahama 805 | Takahashi 806 | Takaki 807 | Takamura 808 | Takano 809 | Takaoka 810 | Takara 811 | Takarabe 812 | Takashi 813 | Takashita 814 | Takasu 815 | Takasugi 816 | Takayama 817 | Takecare 818 | Takeda 819 | Takei 820 | Takekawa 821 | Takemago 822 | Takemitsu 823 | Takemura 824 | Takenouchi 825 | Takeshita 826 | Taketomo 827 | Takeuchi 828 | Takewaki 829 | Takimoto 830 | Takishida 831 | Takishita 832 | Takizawa 833 | Taku 834 | Takudo 835 | Takudome 836 | Tamazaki 837 | Tamura 838 | Tamuro 839 | Tanaka 840 | Tange 841 | Tani 842 | Taniguchi 843 | Tanizaki 844 | Tankoshitsu 845 | Tansho 846 | Tanuma 847 | Tarumi 848 | Tatenaka 849 | Tatsuko 850 | Tatsuno 851 | Tatsuya 852 | Tawaraya 853 | Tayama 854 | Temko 855 | Tenshin 856 | Terada 857 | Terajima 858 | Terakado 859 | Terauchi 860 | Teshigahara 861 | Teshima 862 | Tochikura 863 | Togo 864 | Tojo 865 | Tokaji 866 | Tokuda 867 | Tokudome 868 | Tokuoka 869 | Tomika 870 | Tomimoto 871 | Tomioka 872 | Tommii 873 | Tomonaga 874 | Tomori 875 | Tono 876 | Torii 877 | Torisei 878 | Toru 879 | Toshishai 880 | Toshitala 881 | Toshusai 882 | Toyama 883 | Toyoda 884 | Toyoshima 885 | Toyota 886 | Toyotomi 887 | Tsubouchi 888 | Tsucgimoto 889 | Tsuchie 890 | Tsuda 891 | Tsuji 892 | Tsujimoto 893 | Tsujimura 894 | Tsukada 895 | Tsukade 896 | Tsukahara 897 | Tsukamoto 898 | Tsukatani 899 | Tsukawaki 900 | Tsukehara 901 | Tsukioka 902 | Tsumemasa 903 | Tsumura 904 | Tsunoda 905 | Tsurimi 906 | Tsuruga 907 | Tsuruya 908 | Tsushima 909 | Tsutaya 910 | Tsutomu 911 | Uboshita 912 | Uchida 913 | Uchiyama 914 | Ueda 915 | Uehara 916 | Uemura 917 | Ueshima 918 | Uesugi 919 | Uetake 920 | Ugaki 921 | Ui 922 | Ukiyo 923 | Umari 924 | Umehara 925 | Umeki 926 | Uno 927 | Uoya 928 | Urogataya 929 | Usami 930 | Ushiba 931 | Utagawa 932 | Wakai 933 | Wakatsuki 934 | Watabe 935 | Watanabe 936 | Watari 937 | Watnabe 938 | Watoga 939 | Yakuta 940 | Yamabe 941 | Yamada 942 | Yamagata 943 | Yamaguchi 944 | Yamaguchiya 945 | Yamaha 946 | Yamahata 947 | Yamakage 948 | Yamakawa 949 | Yamakazi 950 | Yamamoto 951 | Yamamura 952 | Yamana 953 | Yamanaka 954 | Yamanouchi 955 | Yamanoue 956 | Yamaoka 957 | Yamashita 958 | Yamato 959 | Yamawaki 960 | Yamazaki 961 | Yamhata 962 | Yamura 963 | Yanagawa 964 | Yanagi 965 | Yanagimoto 966 | Yanagita 967 | Yano 968 | Yasuda 969 | Yasuhiro 970 | Yasui 971 | Yasujiro 972 | Yasukawa 973 | Yasutake 974 | Yoemon 975 | Yokokawa 976 | Yokoyama 977 | Yonai 978 | Yosano 979 | Yoshida 980 | Yoshifumi 981 | Yoshihara 982 | Yoshikawa 983 | Yoshimatsu 984 | Yoshinobu 985 | Yoshioka 986 | Yoshitomi 987 | Yoshizaki 988 | Yoshizawa 989 | Yuasa 990 | Yuhara 991 | Yunokawa 992 | -------------------------------------------------------------------------------- /data/names/Korean.txt: -------------------------------------------------------------------------------- 1 | Ahn 2 | Baik 3 | Bang 4 | Byon 5 | Cha 6 | Chang 7 | Chi 8 | Chin 9 | Cho 10 | Choe 11 | Choi 12 | Chong 13 | Chou 14 | Chu 15 | Chun 16 | Chung 17 | Chweh 18 | Gil 19 | Gu 20 | Gwang 21 | Ha 22 | Han 23 | Ho 24 | Hong 25 | Hung 26 | Hwang 27 | Hyun 28 | Jang 29 | Jeon 30 | Jeong 31 | Jo 32 | Jon 33 | Jong 34 | Jung 35 | Kang 36 | Kim 37 | Ko 38 | Koo 39 | Ku 40 | Kwak 41 | Kwang 42 | Lee 43 | Li 44 | Lim 45 | Ma 46 | Mo 47 | Moon 48 | Nam 49 | Ngai 50 | Noh 51 | Oh 52 | Pae 53 | Pak 54 | Park 55 | Ra 56 | Rhee 57 | Rheem 58 | Ri 59 | Rim 60 | Ron 61 | Ryom 62 | Ryoo 63 | Ryu 64 | San 65 | Seo 66 | Seok 67 | Shim 68 | Shin 69 | Shon 70 | Si 71 | Sin 72 | So 73 | Son 74 | Song 75 | Sook 76 | Suh 77 | Suk 78 | Sun 79 | Sung 80 | Tsai 81 | Wang 82 | Woo 83 | Yang 84 | Yeo 85 | Yeon 86 | Yi 87 | Yim 88 | Yoo 89 | Yoon 90 | You 91 | Youj 92 | Youn 93 | Yu 94 | Yun 95 | -------------------------------------------------------------------------------- /data/names/Polish.txt: -------------------------------------------------------------------------------- 1 | Adamczak 2 | Adamczyk 3 | Andrysiak 4 | Auttenberg 5 | Bartosz 6 | Bernard 7 | Bobienski 8 | Bosko 9 | Broż 10 | Brzezicki 11 | Budny 12 | Bukoski 13 | Bukowski 14 | Chlebek 15 | Chmiel 16 | Czajka 17 | Czajkowski 18 | Dubanowski 19 | Dubicki 20 | Dunajski 21 | Dziedzic 22 | Fabian 23 | Filipek 24 | Filipowski 25 | Gajos 26 | Gniewek 27 | Gomolka 28 | Gomulka 29 | Gorecki 30 | Górka 31 | Górski 32 | Grzeskiewicz 33 | Gwozdek 34 | Jagoda 35 | Janda 36 | Janowski 37 | Jaskolski 38 | Jaskulski 39 | Jedynak 40 | Jelen 41 | Jez 42 | Jordan 43 | Kaczka 44 | Kaluza 45 | Kamiński 46 | Kasprzak 47 | Kava 48 | Kedzierski 49 | Kijek 50 | Klimek 51 | Kosmatka 52 | Kowalczyk 53 | Kowalski 54 | Koziol 55 | Kozlow 56 | Kozlowski 57 | Krakowski 58 | Król 59 | Kumiega 60 | Lawniczak 61 | Lis 62 | Majewski 63 | Malinowski 64 | Maly 65 | Marek 66 | Marszałek 67 | Maslanka 68 | Mencher 69 | Miazga 70 | Michel 71 | Mikolajczak 72 | Mozdzierz 73 | Niemczyk 74 | Niemec 75 | Nosek 76 | Nowak 77 | Pakulski 78 | Pasternack 79 | Pasternak 80 | Paszek 81 | Piatek 82 | Piontek 83 | Pokorny 84 | Poplawski 85 | Róg 86 | Rudaski 87 | Rudawski 88 | Rusnak 89 | Rutkowski 90 | Sadowski 91 | Salomon 92 | Serafin 93 | Sienkiewicz 94 | Sierzant 95 | Sitko 96 | Skala 97 | Slaski 98 | Ślązak 99 | Ślusarczyk 100 | Ślusarski 101 | Smolák 102 | Sniegowski 103 | Sobol 104 | Sokal 105 | Sokolof 106 | Sokoloff 107 | Sokolofsky 108 | Sokolowski 109 | Sokolsky 110 | Sówka 111 | Stanek 112 | Starek 113 | Stawski 114 | Stolarz 115 | Szczepanski 116 | Szewc 117 | Szwarc 118 | Szweda 119 | Szwedko 120 | Walentowicz 121 | Warszawski 122 | Wawrzaszek 123 | Wiater 124 | Winograd 125 | Winogrodzki 126 | Wojda 127 | Wojewódka 128 | Wojewódzki 129 | Wronski 130 | Wyrick 131 | Wyrzyk 132 | Zabek 133 | Zawisza 134 | Zdunowski 135 | Zdunowski 136 | Zielinski 137 | Ziemniak 138 | Zientek 139 | Żuraw 140 | -------------------------------------------------------------------------------- /data/names/Portuguese.txt: -------------------------------------------------------------------------------- 1 | Abreu 2 | Albuquerque 3 | Almeida 4 | Alves 5 | Araújo 6 | Araullo 7 | Barros 8 | Basurto 9 | Belo 10 | Cabral 11 | Campos 12 | Cardozo 13 | Castro 14 | Coelho 15 | Costa 16 | Crespo 17 | Cruz 18 | D'cruz 19 | D'cruze 20 | Delgado 21 | De santigo 22 | Duarte 23 | Estéves 24 | Fernandes 25 | Ferreira 26 | Ferreiro 27 | Ferro 28 | Fonseca 29 | Franco 30 | Freitas 31 | Garcia 32 | Gaspar 33 | Gomes 34 | Gouveia 35 | Guerra 36 | Henriques 37 | Lobo 38 | Machado 39 | Madeira 40 | Magalhães 41 | Maria 42 | Mata 43 | Mateus 44 | Matos 45 | Medeiros 46 | Melo 47 | Mendes 48 | Moreno 49 | Nunes 50 | Palmeiro 51 | Paredes 52 | Pereira 53 | Pinheiro 54 | Pinho 55 | Ramires 56 | Ribeiro 57 | Rios 58 | Rocha 59 | Rodrigues 60 | Romão 61 | Rosario 62 | Salazar 63 | Santana 64 | Santiago 65 | Santos 66 | Serafim 67 | Silva 68 | Silveira 69 | Simões 70 | Soares 71 | Souza 72 | Torres 73 | Vargas 74 | Ventura 75 | -------------------------------------------------------------------------------- /data/names/Scottish.txt: -------------------------------------------------------------------------------- 1 | Smith 2 | Brown 3 | Wilson 4 | Campbell 5 | Stewart 6 | Thomson 7 | Robertson 8 | Anderson 9 | Macdonald 10 | Scott 11 | Reid 12 | Murray 13 | Taylor 14 | Clark 15 | Ross 16 | Watson 17 | Morrison 18 | Paterson 19 | Young 20 | Mitchell 21 | Walker 22 | Fraser 23 | Miller 24 | Mcdonald 25 | Gray 26 | Henderson 27 | Hamilton 28 | Johnston 29 | Duncan 30 | Graham 31 | Ferguson 32 | Kerr 33 | Davidson 34 | Bell 35 | Cameron 36 | Kelly 37 | Martin 38 | Hunter 39 | Allan 40 | Mackenzie 41 | Grant 42 | Simpson 43 | Mackay 44 | Mclean 45 | Macleod 46 | Black 47 | Russell 48 | Marshall 49 | Wallace 50 | Gibson 51 | Kennedy 52 | Gordon 53 | Burns 54 | Sutherland 55 | Stevenson 56 | Munro 57 | Milne 58 | Watt 59 | Murphy 60 | Craig 61 | Wood 62 | Muir 63 | Wright 64 | Mckenzie 65 | Ritchie 66 | Johnstone 67 | Sinclair 68 | White 69 | Mcmillan 70 | Williamson 71 | Dickson 72 | Hughes 73 | Cunningham 74 | Mckay 75 | Bruce 76 | Millar 77 | Crawford 78 | Mcintosh 79 | Douglas 80 | Docherty 81 | King 82 | Jones 83 | Boyle 84 | Fleming 85 | Mcgregor 86 | Aitken 87 | Christie 88 | Shaw 89 | Maclean 90 | Jamieson 91 | Mcintyre 92 | Hay 93 | Lindsay 94 | Alexander 95 | Ramsay 96 | Mccallum 97 | Whyte 98 | Jackson 99 | Mclaughlin 100 | Hill 101 | -------------------------------------------------------------------------------- /data/names/Spanish.txt: -------------------------------------------------------------------------------- 1 | Abana 2 | Abano 3 | Abarca 4 | Abaroa 5 | Abascal 6 | Abasolo 7 | Abel 8 | Abelló 9 | Aberquero 10 | Abreu 11 | Acosta 12 | Agramunt 13 | Aiza 14 | Alamilla 15 | Albert 16 | Albuquerque 17 | Aldana 18 | Alfaro 19 | Alvarado 20 | Álvarez 21 | Alves 22 | Amador 23 | Andreu 24 | Antúnez 25 | Aqua 26 | Aquino 27 | Araújo 28 | Araullo 29 | Araya 30 | Arce 31 | Arechavaleta 32 | Arena 33 | Aritza 34 | Armando 35 | Arreola 36 | Arriola 37 | Asis 38 | Asturias 39 | Avana 40 | Azarola 41 | Banderas 42 | Barros 43 | Basurto 44 | Bautista 45 | Bello 46 | Belmonte 47 | Bengochea 48 | Benitez 49 | Bermúdez 50 | Blanco 51 | Blanxart 52 | Bolívar 53 | Bonaventura 54 | Bosque 55 | Bustillo 56 | Busto 57 | Bustos 58 | Cabello 59 | Cabrera 60 | Campo 61 | Campos 62 | Capello 63 | Cardona 64 | Caro 65 | Casales 66 | Castell 67 | Castellano 68 | Castillion 69 | Castillo 70 | Castro 71 | Chavarría 72 | Chavez 73 | Colón 74 | Costa 75 | Crespo 76 | Cruz 77 | Cuéllar 78 | Cuevas 79 | D'cruz 80 | D'cruze 81 | De la cruz 82 | De la fuente 83 | Del bosque 84 | De leon 85 | Delgado 86 | Del olmo 87 | De santigo 88 | Díaz 89 | Dominguez 90 | Duarte 91 | Durante 92 | Echevarría 93 | Echeverría 94 | Elizondo 95 | Escamilla 96 | Escárcega 97 | Escarrà 98 | Esparza 99 | Espina 100 | Espino 101 | Espinosa 102 | Espinoza 103 | Estévez 104 | Etxebarria 105 | Etxeberria 106 | Félix 107 | Fernández 108 | Ferrer 109 | Fierro 110 | Flores 111 | Fonseca 112 | Franco 113 | Fuentes 114 | Gallego 115 | Gallo 116 | García 117 | Garrastazu 118 | Garza 119 | Gaspar 120 | Gebara 121 | Gomez 122 | Gonzales 123 | Gonzalez 124 | Grec 125 | Guadarrama 126 | Guerra 127 | Guerrero 128 | Gutiérrez 129 | Gutierrez 130 | Hernandez 131 | Herrera 132 | Herrero 133 | Hierro 134 | Holguín 135 | Huerta 136 | Ibáñez 137 | Ibarra 138 | Iñíguez 139 | Iturburua 140 | Jaso 141 | Jasso 142 | Jimenez 143 | Jordà 144 | Juárez 145 | Lobo 146 | Lopez 147 | Losa 148 | Loyola 149 | Machado 150 | Macías 151 | Maradona 152 | María 153 | Marino 154 | Márquez 155 | Martell 156 | Martí 157 | Martínez 158 | Martinez 159 | Mas 160 | Mata 161 | Mateu 162 | Medina 163 | Melendez 164 | Méndez 165 | Mendoza 166 | Menendez 167 | Merlo 168 | Michel 169 | Mingo 170 | Moles 171 | Molina 172 | Montero 173 | Morales 174 | Moralez 175 | Moreno 176 | Narváez 177 | Nieves 178 | Noguerra 179 | Núñez 180 | Obando 181 | Ochoa 182 | Ojeda 183 | Ola 184 | Oleastro 185 | Olguin 186 | Oliver 187 | Olmos 188 | Oquendo 189 | Orellana 190 | Oriol 191 | Ortega 192 | Ortiz 193 | Palomo 194 | Paredes 195 | Pavia 196 | Peláez 197 | Peña 198 | Pérez 199 | Perez 200 | Petit 201 | Picasso 202 | Porra 203 | Porras 204 | Prieto 205 | Puerta 206 | Puga 207 | Puig 208 | Quinones 209 | Quintana 210 | Quirós 211 | Ramírez 212 | Ramos 213 | Rana 214 | Rendón 215 | Rey 216 | Reyes 217 | Rios 218 | Rivera 219 | Rivero 220 | Robledo 221 | Robles 222 | Rocha 223 | Rodríguez 224 | Rodriquez 225 | Roig 226 | Rojas 227 | Rojo 228 | Roldán 229 | Romà 230 | Romà 231 | Romero 232 | Rosa 233 | Rosales 234 | Rubio 235 | Ruiz 236 | Sala 237 | Salamanca 238 | Salazar 239 | Salcedo 240 | Salinas 241 | Sanchez 242 | Sandoval 243 | San nicolas 244 | Santana 245 | Santiago 246 | Santillian 247 | Santos 248 | Sastre 249 | Sepúlveda 250 | Sierra 251 | Silva 252 | Soler 253 | Solo 254 | Solos 255 | Soto 256 | Suárez 257 | Suero 258 | Tapia 259 | Terrazas 260 | Tomàs 261 | Torres 262 | Tos 263 | Tosell 264 | Toset 265 | Travieso 266 | Trujillo 267 | Ubina 268 | Urbina 269 | Ureña 270 | Valdez 271 | Valencia 272 | Varela 273 | Vargas 274 | Vásquez 275 | Vázquez 276 | Vega 277 | Vela 278 | Vela 279 | Velazquez 280 | Ventura 281 | Vicario 282 | Vilaró 283 | Villa 284 | Villalobos 285 | Villanueva 286 | Villaverde 287 | Viola 288 | Viteri 289 | Vivas 290 | Vives 291 | Ybarra 292 | Zabala 293 | Zambrano 294 | Zamorano 295 | Zapatero 296 | Zavala 297 | Zubizarreta 298 | Zuñiga 299 | -------------------------------------------------------------------------------- /data/names/Vietnamese.txt: -------------------------------------------------------------------------------- 1 | Nguyen 2 | Tron 3 | Le 4 | Pham 5 | Huynh 6 | Hoang 7 | Phan 8 | Vu 9 | Vo 10 | Dang 11 | Bui 12 | Do 13 | Ho 14 | Ngo 15 | Duong 16 | Ly 17 | An 18 | an 19 | Bach 20 | Banh 21 | Cao 22 | Chau 23 | Chu 24 | Chung 25 | Chu 26 | Diep 27 | Doan 28 | Dam 29 | Dao 30 | Dinh 31 | Doan 32 | Giang 33 | Ha 34 | Han 35 | Kieu 36 | Kim 37 | La 38 | Lac 39 | Lam 40 | Lieu 41 | Luc 42 | Luong 43 | Luu 44 | Ma 45 | Mach 46 | Mai 47 | Nghiem 48 | Phi 49 | Pho 50 | Phung 51 | Quach 52 | Quang 53 | Quyen 54 | Ta 55 | Thach 56 | Thai 57 | Sai 58 | Thi 59 | Than 60 | Thao 61 | Thuy 62 | Tieu 63 | To 64 | Ton 65 | Tong 66 | Trang 67 | Trieu 68 | Trinh 69 | Truong 70 | Van 71 | Vinh 72 | Vuong 73 | Vuu 74 | -------------------------------------------------------------------------------- /data_loader.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | from torch.utils.data import DataLoader, Dataset 3 | import torch.autograd as autograd 4 | import torch 5 | import json 6 | import csv 7 | 8 | class AGNEWs(Dataset): 9 | def __init__(self, label_data_path, alphabet_path, l0 = 1014): 10 | """Create AG's News dataset object. 11 | 12 | Arguments: 13 | label_data_path: The path of label and data file in csv. 14 | l0: max length of a sample. 15 | alphabet_path: The path of alphabet json file. 16 | """ 17 | self.label_data_path = label_data_path 18 | self.l0 = l0 19 | # read alphabet 20 | self.loadAlphabet(alphabet_path) 21 | self.load(label_data_path) 22 | 23 | 24 | def __len__(self): 25 | return len(self.label) 26 | 27 | 28 | def __getitem__(self, idx): 29 | X = self.oneHotEncode(idx) 30 | y = self.y[idx] 31 | return X, y 32 | 33 | def loadAlphabet(self, alphabet_path): 34 | with open(alphabet_path) as f: 35 | self.alphabet = ''.join(json.load(f)) 36 | 37 | def load(self, label_data_path, lowercase = True): 38 | self.label = [] 39 | self.data = [] 40 | with open(label_data_path, 'r') as f: 41 | rdr = csv.reader(f, delimiter=',', quotechar='"') 42 | # num_samples = sum(1 for row in rdr) 43 | for index, row in enumerate(rdr): 44 | self.label.append(int(row[0])) 45 | txt = ' '.join(row[1:]) 46 | if lowercase: 47 | txt = txt.lower() 48 | self.data.append(txt) 49 | 50 | self.y = torch.LongTensor(self.label) 51 | 52 | 53 | def oneHotEncode(self, idx): 54 | # X = (batch, 70, sequence_length) 55 | X = torch.zeros(len(self.alphabet), self.l0) 56 | sequence = self.data[idx] 57 | for index_char, char in enumerate(sequence[::-1]): 58 | if self.char2Index(char)!=-1: 59 | X[self.char2Index(char)][index_char] = 1.0 60 | return X 61 | 62 | def char2Index(self, character): 63 | return self.alphabet.find(character) 64 | 65 | def getClassWeight(self): 66 | num_samples = self.__len__() 67 | label_set = set(self.label) 68 | num_class = [self.label.count(c) for c in label_set] 69 | class_weight = [num_samples/float(self.label.count(c)) for c in label_set] 70 | return class_weight, num_class 71 | 72 | if __name__ == '__main__': 73 | 74 | label_data_path = 'data/ag_news_csv/test.csv' 75 | alphabet_path = 'alphabet.json' 76 | 77 | train_dataset = AGNEWs(label_data_path, alphabet_path) 78 | train_loader = DataLoader(train_dataset, batch_size=64, num_workers=4, drop_last=False) 79 | 80 | # size = 0 81 | for i_batch, sample_batched in enumerate(train_loader): 82 | if i_batch == 0: 83 | print(sample_batched[0][0][0].shape) 84 | 85 | # print(sample_batched) 86 | # len(i_batch) 87 | # print(sample_batched['label'].size()) 88 | # inputs = sample_batched['data'] 89 | # print(inputs.size()) 90 | # print('type(target): ', target) 91 | 92 | -------------------------------------------------------------------------------- /data_loader_txt.py: -------------------------------------------------------------------------------- 1 | #! /usr/bin/env python 2 | import torchtext.data as data 3 | import torchtext.datasets as datasets 4 | import re 5 | import os 6 | import random 7 | import tarfile 8 | from six.moves import urllib 9 | from torchtext import data 10 | import codecs 11 | 12 | class TarDataset(data.Dataset): 13 | """Defines a Dataset loaded from a downloadable tar archive. 14 | 15 | Attributes: 16 | url: URL where the tar archive can be downloaded. 17 | filename: Filename of the downloaded tar archive. 18 | dirname: Name of the top-level directory within the zip archive that 19 | contains the data files. 20 | """ 21 | 22 | @classmethod 23 | def download_or_unzip(cls, root): 24 | path = os.path.join(root, cls.dirname) 25 | if not os.path.isdir(path): 26 | tpath = os.path.join(root, cls.filename) 27 | if not os.path.isfile(tpath): 28 | print('downloading') 29 | urllib.request.urlretrieve(cls.url, tpath) 30 | with tarfile.open(tpath, 'r') as tfile: 31 | print('extracting') 32 | tfile.extractall(root) 33 | return os.path.join(path, '') 34 | 35 | 36 | class MR(TarDataset): 37 | 38 | url = 'https://www.cs.cornell.edu/people/pabo/movie-review-data/rt-polaritydata.tar.gz' 39 | filename = 'rt-polaritydata.tar' 40 | dirname = 'rt-polaritydata' 41 | 42 | @staticmethod 43 | def sort_key(ex): 44 | return len(ex.text) 45 | 46 | def __init__(self, text_field, label_field, path=None, examples=None, **kwargs): 47 | """Create an MR dataset instance given a path and fields. 48 | 49 | Arguments: 50 | text_field: The field that will be used for text data. 51 | label_field: The field that will be used for label data. 52 | path: Path to the data file. 53 | examples: The examples contain all the data. 54 | Remaining keyword arguments: Passed to the constructor of 55 | data.Dataset. 56 | """ 57 | def clean_str(string): 58 | """ 59 | Tokenization/string cleaning for all datasets except for SST. 60 | Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py 61 | """ 62 | string = re.sub(r"[^A-Za-z0-9(),!?\'\`]", " ", string) 63 | string = re.sub(r"\'s", " \'s", string) 64 | string = re.sub(r"\'ve", " \'ve", string) 65 | string = re.sub(r"n\'t", " n\'t", string) 66 | string = re.sub(r"\'re", " \'re", string) 67 | string = re.sub(r"\'d", " \'d", string) 68 | string = re.sub(r"\'ll", " \'ll", string) 69 | string = re.sub(r",", " , ", string) 70 | string = re.sub(r"!", " ! ", string) 71 | string = re.sub(r"\(", " \( ", string) 72 | string = re.sub(r"\)", " \) ", string) 73 | string = re.sub(r"\?", " \? ", string) 74 | string = re.sub(r"\s{2,}", " ", string) 75 | return string.strip() 76 | 77 | text_field.preprocessing = data.Pipeline(clean_str) 78 | fields = [('text', text_field), ('label', label_field)] 79 | 80 | if examples is None: 81 | path = self.dirname if path is None else path 82 | examples = [] 83 | with codecs.open(os.path.join(path, 'rt-polarity.neg'), encoding='utf-8', errors='ignore') as f: 84 | examples += [ 85 | data.Example.fromlist([line, 'negative'], fields) for line in f] 86 | with codecs.open(os.path.join(path, 'rt-polarity.pos'), encoding='utf-8', errors='ignore') as f: 87 | examples += [ 88 | data.Example.fromlist([line, 'positive'], fields) for line in f] 89 | super(MR, self).__init__(examples, fields, **kwargs) 90 | 91 | @classmethod 92 | def splits(cls, text_field, label_field, dev_ratio=.1, shuffle=True ,root='.', **kwargs): 93 | """Create dataset objects for splits of the MR dataset. 94 | 95 | Arguments: 96 | text_field: The field that will be used for the sentence. 97 | label_field: The field that will be used for label data. 98 | dev_ratio: The ratio that will be used to get split validation dataset. 99 | shuffle: Whether to shuffle the data before split. 100 | root: The root directory that the dataset's zip archive will be 101 | expanded into; therefore the directory in whose trees 102 | subdirectory the data files will be stored. 103 | train: The filename of the train data. Default: 'train.txt'. 104 | Remaining keyword arguments: Passed to the splits method of 105 | Dataset. 106 | """ 107 | path = cls.download_or_unzip(root) 108 | examples = cls(text_field, label_field, path=path, **kwargs).examples 109 | if shuffle: random.shuffle(examples) 110 | dev_index = -1 * int(dev_ratio*len(examples)) 111 | 112 | return (cls(text_field, label_field, examples=examples[:dev_index]), 113 | cls(text_field, label_field, examples=examples[dev_index:])) 114 | 115 | 116 | 117 | # load SST dataset 118 | def sst(text_field, label_field, batch_size, **kargs): 119 | train_data, dev_data, test_data = datasets.SST.splits(text_field, label_field, fine_grained=True) 120 | text_field.build_vocab(train_data, dev_data, test_data) 121 | label_field.build_vocab(train_data, dev_data, test_data) 122 | train_iter, dev_iter, test_iter = data.BucketIterator.splits( 123 | (train_data, dev_data, test_data), 124 | batch_sizes=(batch_size, 125 | len(dev_data), 126 | len(test_data)), 127 | **kargs) 128 | return train_iter, dev_iter, test_iter 129 | 130 | 131 | # load MR dataset 132 | def mr(text_field, label_field, batch_size, **kargs): 133 | train_data, dev_data = MR.splits(text_field, label_field) 134 | text_field.build_vocab(train_data, dev_data) 135 | label_field.build_vocab(train_data, dev_data) 136 | train_iter, dev_iter = data.Iterator.splits( 137 | (train_data, dev_data), 138 | batch_sizes=(batch_size, len(dev_data)), 139 | **kargs) 140 | return train_iter, dev_iter 141 | 142 | 143 | -------------------------------------------------------------------------------- /metric.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | from termcolor import cprint, colored as c 3 | 4 | def inc(d, label): 5 | if label in d: 6 | d[label] += 1 7 | else: 8 | d[label] = 1 9 | 10 | def precision_recall(output, target): 11 | assert len(output) == len(target), "output len: {} != target len: {}".format(len(output), len(target)) 12 | labels = set(target) 13 | TP = {} 14 | TP_plus_FN = {} 15 | TP_plus_FP = {} 16 | for i in range(len(output)): 17 | 18 | inc(TP_plus_FN, target[i]) 19 | inc(TP_plus_FP, output[i]) 20 | if target[i] == output[i]: 21 | inc(TP, output[i]) 22 | 23 | for label in labels: 24 | if label not in TP_plus_FN: 25 | TP_plus_FN[label] = 0 26 | if label not in TP_plus_FP: 27 | TP_plus_FP[label] = 0 28 | 29 | precision = {label: 0. if TP_plus_FP[label] ==0 else ((TP[label] if label in TP else 0) / float(TP_plus_FP[label])) for label in labels} 30 | recall = {label: 0. if TP_plus_FN[label] ==0 else ((TP[label] if label in TP else 0) / float(TP_plus_FN[label])) for label in labels} 31 | 32 | return precision, recall, TP, TP_plus_FN, TP_plus_FP 33 | 34 | 35 | def F_score(p, r): 36 | 37 | f_scores = { 38 | label: None if p[label] == 0 and r[label] == 0 else (0 if p[label] == 0 or r[label] == 0 else 2 / (1 / p[label] + 1 / r[label])) 39 | for label in p 40 | } 41 | return f_scores 42 | 43 | 44 | def print_f_score(output, target): 45 | """returns: 46 | p, 47 | r, 48 | f<-score>, 49 | {"TP", "p", "TP_plus_FP"} """ 50 | p, r, TP, TP_plus_FN, TP_plus_FP = precision_recall(output, target) 51 | f = F_score(p, r) 52 | 53 | # cprint("Label: " + c((" " + str(10))[-5:], 'red') + 54 | # "\tPrec: " + c(" {:.1f}".format(0.335448 * 100)[-5:], 'green') + '%' + 55 | # " ({:d}/{:d})".format(1025, 1254).ljust(14) + 56 | # "Recall: " + c(" {:.1f}".format(0.964 * 100)[-5:], 'green') + "%" + 57 | # " ({:d}/{:d})".format(15, 154).ljust(14) + 58 | # "F-Score: " + (c(" {:.1f}".format(0.5 * 100)[-5:], "green") + "%") 59 | # ) 60 | 61 | for label in f.keys(): 62 | cprint("Label: " + c((" " + str(label))[-5:], 'red') + 63 | "\tPrec: " + c(" {:.1f}".format(p[label] * 100)[-5:], 'green') + '%' + 64 | " ({:d}/{:d})".format((TP[label] if label in TP else 0), TP_plus_FP[label]).ljust(14) + 65 | "Recall: " + c(" {:.1f}".format((r[label] if label in r else 0) * 100)[-5:], 'green') + "%" + 66 | " ({:d}/{:d})".format((TP[label] if label in TP else 0), TP_plus_FN[label]).ljust(14) + 67 | "F-Score: " + (" N/A" if f[label] is None else (c(" {:.1f}".format(f[label] * 100)[-5:], "green") + "%")) 68 | ) 69 | # return p, r, f, _ 70 | 71 | 72 | if __name__ == '__main__': 73 | 74 | import torch 75 | import torch.autograd as autograd 76 | output = [1,1,1,1,1,2,0,2,2,2,2] 77 | output = torch.LongTensor(output) 78 | # target = [0,0,2,1,2,2,1,2,1,2,0] 79 | 80 | target = [1,3,2,3,3,3,3,3,0,3,3] 81 | 82 | target = torch.LongTensor(target) 83 | output = autograd.Variable(output) 84 | target = autograd.Variable(target) 85 | print('output') 86 | print(output.data.numpy().tolist()) 87 | print('target') 88 | print(target.data.numpy().tolist()) 89 | 90 | 91 | precision, recall, TP, TP_plus_FN, TP_plus_FP = precision_recall(output.data.numpy().tolist(), target.data.numpy().tolist()) 92 | print('precision') 93 | print(precision) 94 | print('recall') 95 | print(recall) 96 | print('TP') 97 | print(TP) 98 | print('TP_plus_FN') 99 | print(TP_plus_FN) 100 | print('TP_plus_FP') 101 | print(TP_plus_FP) 102 | # print(dic) 103 | 104 | 105 | f_scores = F_score(precision, recall) 106 | print('f_scores') 107 | print(f_scores) 108 | # print(f_scores.keys()) 109 | 110 | 111 | print('\r') 112 | print_f_score(output.data.numpy().tolist(), target.data.numpy().tolist()) -------------------------------------------------------------------------------- /model.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import torch 3 | import torch.nn as nn 4 | import torch.nn.functional as F 5 | 6 | class CharCNN(nn.Module): 7 | def __init__(self, args): 8 | super(CharCNN, self).__init__() 9 | self.conv1 = nn.Sequential( 10 | nn.Conv1d(args.num_features, 256, kernel_size=7, stride=1), 11 | nn.ReLU(), 12 | nn.MaxPool1d(kernel_size=3, stride=3) 13 | ) 14 | 15 | self.conv2 = nn.Sequential( 16 | nn.Conv1d(256, 256, kernel_size=7, stride=1), 17 | nn.ReLU(), 18 | nn.MaxPool1d(kernel_size=3, stride=3) 19 | ) 20 | 21 | self.conv3 = nn.Sequential( 22 | nn.Conv1d(256, 256, kernel_size=3, stride=1), 23 | nn.ReLU() 24 | ) 25 | 26 | self.conv4 = nn.Sequential( 27 | nn.Conv1d(256, 256, kernel_size=3, stride=1), 28 | nn.ReLU() 29 | ) 30 | 31 | self.conv5 = nn.Sequential( 32 | nn.Conv1d(256, 256, kernel_size=3, stride=1), 33 | nn.ReLU() 34 | ) 35 | 36 | self.conv6 = nn.Sequential( 37 | nn.Conv1d(256, 256, kernel_size=3, stride=1), 38 | nn.ReLU(), 39 | nn.MaxPool1d(kernel_size=3, stride=3) 40 | ) 41 | 42 | 43 | self.fc1 = nn.Sequential( 44 | nn.Linear(8704, 1024), 45 | nn.ReLU(), 46 | nn.Dropout(p=args.dropout) 47 | ) 48 | 49 | self.fc2 = nn.Sequential( 50 | nn.Linear(1024, 1024), 51 | nn.ReLU(), 52 | nn.Dropout(p=args.dropout) 53 | ) 54 | 55 | self.fc3 = nn.Linear(1024, 4) 56 | self.log_softmax = nn.LogSoftmax() 57 | 58 | def forward(self, x): 59 | x = self.conv1(x) 60 | x = self.conv2(x) 61 | x = self.conv3(x) 62 | x = self.conv4(x) 63 | x = self.conv5(x) 64 | x = self.conv6(x) 65 | 66 | # collapse 67 | x = x.view(x.size(0), -1) 68 | # linear layer 69 | x = self.fc1(x) 70 | # linear layer 71 | x = self.fc2(x) 72 | # linear layer 73 | x = self.fc3(x) 74 | # output layer 75 | x = self.log_softmax(x) 76 | 77 | return x -------------------------------------------------------------------------------- /model_CharCNN2D.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import torch 3 | import torch.nn as nn 4 | import torch.nn.functional as F 5 | 6 | # class InferenceBatchLogSoftmax(nn.Module): 7 | # def forward(self, input_): 8 | # batch_size = input_.size()[0] 9 | # return torch.stack([F.log_softmax(input_[i]) for i in range(batch_size)], 0) 10 | 11 | 12 | class CharCNN(nn.Module): 13 | 14 | def __init__(self, num_features): 15 | super(CharCNN, self).__init__() 16 | 17 | self.num_features = num_features 18 | self.conv1 = nn.Sequential( 19 | nn.Conv2d(1, 256, kernel_size=(7, self.num_features), stride=1), 20 | nn.ReLU() 21 | ) 22 | 23 | self.maxpool1 = nn.MaxPool2d(kernel_size=(3, 1), stride=(3, 1)) 24 | 25 | self.conv2 = nn.Sequential( 26 | nn.Conv2d(1, 256, kernel_size=(7, 256), stride=1), 27 | nn.ReLU() 28 | ) 29 | self.maxpool2 = nn.MaxPool2d(kernel_size=(3, 1), stride=(3, 1)) 30 | 31 | self.conv3 = nn.Sequential( 32 | nn.Conv2d(1, 256, kernel_size=(3, 256), stride=1), 33 | nn.ReLU() 34 | ) 35 | 36 | self.conv4 = nn.Sequential( 37 | nn.Conv2d(1, 256, kernel_size=(3, 256), stride=1), 38 | nn.ReLU() 39 | ) 40 | 41 | self.conv5 = nn.Sequential( 42 | nn.Conv2d(1, 256, kernel_size=(3, 256), stride=1), 43 | nn.ReLU() 44 | ) 45 | 46 | self.conv6 = nn.Sequential( 47 | nn.Conv2d(1, 256, kernel_size=(3, 256), stride=1), 48 | nn.ReLU() 49 | ) 50 | 51 | self.maxpool6 = nn.MaxPool2d(kernel_size=(3, 1), stride=(3, 1)) 52 | 53 | self.fc1 = nn.Sequential( 54 | nn.Linear(8704, 1024), 55 | nn.ReLU(), 56 | nn.Dropout(p=0.5) 57 | ) 58 | self.fc2 = nn.Sequential( 59 | nn.Linear(1024, 1024), 60 | nn.ReLU(), 61 | nn.Dropout(p=0.5) 62 | ) 63 | self.fc3 =nn.Linear(1024, 4) 64 | self.softmax = nn.LogSoftmax() 65 | # nn.LogSoftmax() 66 | 67 | # self.inference_log_softmax = InferenceBatchLogSoftmax() 68 | 69 | def forward(self, x): 70 | debug=False 71 | x = x.unsqueeze(1) 72 | if debug: 73 | print('x.size()', x.size()) 74 | 75 | x = self.conv1(x) 76 | if debug: 77 | print('x after conv1', x.size()) 78 | 79 | x = x.transpose(1,3) 80 | if debug: 81 | print('x after transpose', x.size()) 82 | 83 | x = self.maxpool1(x) 84 | if debug: 85 | print('x after maxpool1', x.size()) 86 | 87 | x = self.conv2(x) 88 | if debug: 89 | print('x after conv2', x.size()) 90 | 91 | x = x.transpose(1,3) 92 | if debug: 93 | print('x after transpose', x.size()) 94 | 95 | x = self.maxpool2(x) 96 | if debug: 97 | print('x after maxpool2', x.size()) 98 | 99 | x = self.conv3(x) 100 | if debug: 101 | print('x after conv3', x.size()) 102 | 103 | x = x.transpose(1,3) 104 | if debug: 105 | print('x after transpose', x.size()) 106 | 107 | 108 | x = self.conv4(x) 109 | if debug: 110 | print('x after conv4', x.size()) 111 | 112 | x = x.transpose(1,3) 113 | if debug: 114 | print('x after transpose', x.size()) 115 | 116 | 117 | x = self.conv5(x) 118 | if debug: 119 | print('x after conv5', x.size()) 120 | 121 | x = x.transpose(1,3) 122 | if debug: 123 | print('x after transpose', x.size()) 124 | 125 | 126 | x = self.conv6(x) 127 | if debug: 128 | print('x after conv6', x.size()) 129 | 130 | x = x.transpose(1,3) 131 | if debug: 132 | print('x after transpose', x.size()) 133 | 134 | 135 | x = self.maxpool6(x) 136 | if debug: 137 | print('x after maxpool6', x.size()) 138 | 139 | x = x.view(x.size(0), -1) 140 | if debug: 141 | print('Collapse x:, ', x.size()) 142 | 143 | x = self.fc1(x) 144 | if debug: 145 | print('FC1: ', x.size()) 146 | 147 | x = self.fc2(x) 148 | if debug: 149 | print('FC2: ', x.size()) 150 | 151 | x = self.fc3(x) 152 | if debug: 153 | print('x: ', x.size()) 154 | 155 | x = self.softmax(x) 156 | # x = self.inference_log_softmax(x) 157 | 158 | return x -------------------------------------------------------------------------------- /model_SentCNN.py: -------------------------------------------------------------------------------- 1 | import torch 2 | import torch.nn as nn 3 | import torch.nn.functional as F 4 | 5 | class CNN_Text(nn.Module): 6 | 7 | def __init__(self, args): 8 | super(CNN_Text,self).__init__() 9 | self.args = args 10 | 11 | V = args.embed_num 12 | D = args.embed_dim 13 | C = args.class_num 14 | Ci = 1 15 | Co = args.kernel_num 16 | Ks = args.kernel_sizes 17 | 18 | self.embed = nn.Embedding(V, D) 19 | #self.convs1 = [nn.Conv2d(Ci, Co, (K, D)) for K in Ks] 20 | self.convs1 = nn.ModuleList([nn.Conv2d(Ci, Co, (K, D)) for K in Ks]) 21 | ''' 22 | self.conv13 = nn.Conv2d(Ci, Co, (3, D)) 23 | self.conv14 = nn.Conv2d(Ci, Co, (4, D)) 24 | self.conv15 = nn.Conv2d(Ci, Co, (5, D)) 25 | ''' 26 | self.dropout = nn.Dropout(args.dropout) 27 | self.fc1 = nn.Linear(len(Ks)*Co, C) 28 | 29 | def conv_and_pool(self, x, conv): 30 | x = F.relu(conv(x)).squeeze(3) #(N,Co,W) 31 | x = F.max_pool1d(x, x.size(2)).squeeze(2) 32 | return x 33 | 34 | 35 | def forward(self, x): 36 | x = self.embed(x) # (N,W,D) 37 | 38 | if self.args.static: 39 | x = Variable(x) 40 | 41 | x = x.unsqueeze(1) # (N,Ci,W,D) 42 | 43 | x = [F.relu(conv(x)).squeeze(3) for conv in self.convs1] #[(N,Co,W), ...]*len(Ks) 44 | 45 | 46 | x = [F.max_pool1d(i, i.size(2)).squeeze(2) for i in x] #[(N,Co), ...]*len(Ks) 47 | 48 | x = torch.cat(x, 1) 49 | 50 | ''' 51 | x1 = self.conv_and_pool(x,self.conv13) #(N,Co) 52 | x2 = self.conv_and_pool(x,self.conv14) #(N,Co) 53 | x3 = self.conv_and_pool(x,self.conv15) #(N,Co) 54 | x = torch.cat((x1, x2, x3), 1) # (N,len(Ks)*Co) 55 | ''' 56 | x = self.dropout(x) # (N,len(Ks)*Co) 57 | logit = self.fc1(x) # (N,C) 58 | return logit 59 | -------------------------------------------------------------------------------- /mydatasets.py: -------------------------------------------------------------------------------- 1 | import re 2 | import os 3 | import random 4 | import tarfile 5 | from six.moves import urllib 6 | from torchtext import data 7 | import codecs 8 | import mydatasets 9 | 10 | class TarDataset(data.Dataset): 11 | """Defines a Dataset loaded from a downloadable tar archive. 12 | 13 | Attributes: 14 | url: URL where the tar archive can be downloaded. 15 | filename: Filename of the downloaded tar archive. 16 | dirname: Name of the top-level directory within the zip archive that 17 | contains the data files. 18 | """ 19 | 20 | @classmethod 21 | def download_or_unzip(cls, root): 22 | path = os.path.join(root, cls.dirname) 23 | if not os.path.isdir(path): 24 | tpath = os.path.join(root, cls.filename) 25 | if not os.path.isfile(tpath): 26 | print('downloading') 27 | urllib.request.urlretrieve(cls.url, tpath) 28 | with tarfile.open(tpath, 'r') as tfile: 29 | print('extracting') 30 | tfile.extractall(root) 31 | return os.path.join(path, '') 32 | 33 | 34 | class MR(TarDataset): 35 | 36 | url = 'https://www.cs.cornell.edu/people/pabo/movie-review-data/rt-polaritydata.tar.gz' 37 | filename = 'rt-polaritydata.tar' 38 | dirname = 'rt-polaritydata' 39 | 40 | @staticmethod 41 | def sort_key(ex): 42 | return len(ex.text) 43 | 44 | def __init__(self, text_field, label_field, path=None, examples=None, **kwargs): 45 | """Create an MR dataset instance given a path and fields. 46 | 47 | Arguments: 48 | text_field: The field that will be used for text data. 49 | label_field: The field that will be used for label data. 50 | path: Path to the data file. 51 | examples: The examples contain all the data. 52 | Remaining keyword arguments: Passed to the constructor of 53 | data.Dataset. 54 | """ 55 | def clean_str(string): 56 | """ 57 | Tokenization/string cleaning for all datasets except for SST. 58 | Original taken from https://github.com/yoonkim/CNN_sentence/blob/master/process_data.py 59 | """ 60 | string = re.sub(r"[^A-Za-z0-9(),!?\'\`]", " ", string) 61 | string = re.sub(r"\'s", " \'s", string) 62 | string = re.sub(r"\'ve", " \'ve", string) 63 | string = re.sub(r"n\'t", " n\'t", string) 64 | string = re.sub(r"\'re", " \'re", string) 65 | string = re.sub(r"\'d", " \'d", string) 66 | string = re.sub(r"\'ll", " \'ll", string) 67 | string = re.sub(r",", " , ", string) 68 | string = re.sub(r"!", " ! ", string) 69 | string = re.sub(r"\(", " \( ", string) 70 | string = re.sub(r"\)", " \) ", string) 71 | string = re.sub(r"\?", " \? ", string) 72 | string = re.sub(r"\s{2,}", " ", string) 73 | return string.strip() 74 | 75 | text_field.preprocessing = data.Pipeline(clean_str) 76 | fields = [('text', text_field), ('label', label_field)] 77 | 78 | if examples is None: 79 | path = self.dirname if path is None else path 80 | examples = [] 81 | with codecs.open(os.path.join(path, 'rt-polarity.neg'), encoding='utf-8', errors='ignore') as f: 82 | examples += [ 83 | data.Example.fromlist([line, 'negative'], fields) for line in f] 84 | with codecs.open(os.path.join(path, 'rt-polarity.pos'), encoding='utf-8', errors='ignore') as f: 85 | examples += [ 86 | data.Example.fromlist([line, 'positive'], fields) for line in f] 87 | super(MR, self).__init__(examples, fields, **kwargs) 88 | 89 | @classmethod 90 | def splits(cls, text_field, label_field, dev_ratio=.1, shuffle=True ,root='.', **kwargs): 91 | """Create dataset objects for splits of the MR dataset. 92 | 93 | Arguments: 94 | text_field: The field that will be used for the sentence. 95 | label_field: The field that will be used for label data. 96 | dev_ratio: The ratio that will be used to get split validation dataset. 97 | shuffle: Whether to shuffle the data before split. 98 | root: The root directory that the dataset's zip archive will be 99 | expanded into; therefore the directory in whose trees 100 | subdirectory the data files will be stored. 101 | train: The filename of the train data. Default: 'train.txt'. 102 | Remaining keyword arguments: Passed to the splits method of 103 | Dataset. 104 | """ 105 | path = cls.download_or_unzip(root) 106 | examples = cls(text_field, label_field, path=path, **kwargs).examples 107 | if shuffle: random.shuffle(examples) 108 | dev_index = -1 * int(dev_ratio*len(examples)) 109 | 110 | return (cls(text_field, label_field, examples=examples[:dev_index]), 111 | cls(text_field, label_field, examples=examples[dev_index:])) 112 | -------------------------------------------------------------------------------- /predict.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | import os 3 | import argparse 4 | import datetime 5 | import sys 6 | import errno 7 | import model_CharCNN 8 | from data_loader import AGNEWs 9 | from torch.utils.data import DataLoader 10 | import torch 11 | from torch import nn 12 | import torch.autograd as autograd 13 | import torch.nn.functional as F 14 | 15 | 16 | parser = argparse.ArgumentParser(description='Character level CNN text classifier inference') 17 | # data 18 | parser.add_argument('-val-path', metavar='DIR', 19 | help='path to validating data csv', default='data/ag_news_csv/test.csv') 20 | parser.add_argument('-alphabet-path', default='alphabet.json', help='Contains all characters for prediction') 21 | 22 | # device 23 | 24 | parser.add_argument('-device', type=int, default=-1, help='device to use for iterate data, -1 mean cpu [default: -1]') 25 | parser.add_argument('-cuda', action='store_true', default=True, help='enable the gpu' ) 26 | # logging options 27 | parser.add_argument('-verbose', dest='verbose', action='store_true', default=False, help='Turn on progress tracking per iteration for debugging') 28 | parser.add_argument('-checkpoint', dest='checkpoint', default=True, action='store_true', help='Enables checkpoint saving of model') 29 | parser.add_argument('-save-folder', default='models/', help='Location to save epoch models') 30 | parser.add_argument('-log-interval', type=int, default=1, help='how many steps to wait before logging training status [default: 1]') 31 | parser.add_argument('-test-interval', type=int, default=100, help='how many steps to wait before vaidating [default: 100]') 32 | parser.add_argument('-save-interval', type=int, default=20, help='how many epochs to wait before saving [default:10]') 33 | 34 | 35 | else : 36 | print('\nLoading model from [%s]...' % args.snapshot) 37 | try: 38 | cnn = torch.load(args.snapshot) 39 | except : 40 | print("Sorry, This snapshot doesn't exist."); exit() 41 | 42 | 43 | if args.predict is not None: 44 | label = train.predict(args.predict, cnn, text_field, label_field) 45 | print('\n[Text] {}[Label] {}\n'.format(args.predict, label)) 46 | 47 | 48 | 49 | def predict(text, model, text_field, label_feild): 50 | assert isinstance(text, str) 51 | model.eval() 52 | text = text_field.tokenize(text) 53 | text = text_field.preprocess(text) 54 | text = [[text_field.vocab.stoi[x] for x in text]] 55 | x = text_field.tensor_type(text) 56 | x = autograd.Variable(x, volatile=True) 57 | print(x) 58 | output = model(x) 59 | _, predicted = torch.max(output, 1) 60 | return label_feild.vocab.itos[predicted.data[0][0]+1] 61 | 62 | if __name__ == '__main__': 63 | model = DeepSpeech.load_model(args.model_path, cuda=args.cuda) 64 | model.eval() 65 | 66 | labels = DeepSpeech.get_labels(model) 67 | audio_conf = DeepSpeech.get_audio_conf(model) 68 | 69 | if args.decoder == "beam": 70 | scorer = None 71 | if args.lm_path is not None: 72 | scorer = KenLMScorer(labels, args.lm_path, args.trie_path) 73 | scorer.set_lm_weight(args.lm_alpha) 74 | scorer.set_word_weight(args.lm_beta1) 75 | scorer.set_valid_word_weight(args.lm_beta2) 76 | else: 77 | scorer = Scorer() 78 | decoder = BeamCTCDecoder(labels, scorer, beam_width=args.beam_width, top_paths=1, space_index=labels.index(' '), blank_index=labels.index('_')) 79 | else: 80 | decoder = GreedyDecoder(labels, space_index=labels.index(' '), blank_index=labels.index('\'')) 81 | 82 | audio_paths = [] 83 | if os.path.isdir(args.audio_path): 84 | audio_paths = glob.glob(args.audio_path+os.sep+'*.wav') 85 | else: 86 | audio_paths.append(args.audio_path) 87 | 88 | parser = SpectrogramParser(audio_conf, normalize=True) 89 | 90 | for audio_path in audio_paths: 91 | t0 = time.time() 92 | spect = parser.parse_audio(audio_path).contiguous() 93 | spect = spect.view(1, 1, spect.size(0), spect.size(1)) 94 | out = model(Variable(spect, volatile=True)) 95 | out = out.transpose(0, 1) # TxNxH 96 | 97 | if args.prob: 98 | out_numpy = out.data.cpu().numpy() 99 | t1 = time.time() 100 | print(out_numpy) 101 | else: 102 | decoded_output = decoder.decode(out.data) 103 | t1 = time.time() 104 | print(decoded_output[0]) 105 | 106 | print("Decoded {0:.2f} seconds of audio in {1:.2f} seconds\n".format(spect.size(3)*audio_conf['window_stride'], t1-t0)) -------------------------------------------------------------------------------- /test.py: -------------------------------------------------------------------------------- 1 | import os 2 | import argparse 3 | import datetime 4 | import sys 5 | import errno 6 | from model import CharCNN 7 | from data_loader import AGNEWs 8 | from torch.utils.data import DataLoader 9 | import torch 10 | from torch import nn 11 | from torch.autograd import Variable 12 | import torch.nn.functional as F 13 | from metric import print_f_score 14 | 15 | parser = argparse.ArgumentParser(description='Character level CNN text classifier testing', formatter_class=argparse.RawTextHelpFormatter) 16 | # model 17 | parser.add_argument('--model-path', default=None, help='Path to pre-trained acouctics model created by DeepSpeech training') 18 | parser.add_argument('--dropout', type=float, default=0.5, help='the probability for dropout [default: 0.5]') 19 | parser.add_argument('--l0', type=int, default=1014, help='maximum length of input sequence to CNNs [default: 1014]') 20 | parser.add_argument('--kernel-num', type=int, default=100, help='number of each kind of kernel') 21 | parser.add_argument('--kernel-sizes', type=str, default='3,4,5', help='comma-separated kernel size to use for convolution') 22 | # data 23 | parser.add_argument('--test-path', metavar='DIR', 24 | help='path to testing data csv', default='data/ag_news_csv/test.csv') 25 | parser.add_argument('--batch-size', type=int, default=20, help='batch size for training [default: 128]') 26 | parser.add_argument('--alphabet-path', default='alphabet.json', help='Contains all characters for prediction') 27 | # device 28 | parser.add_argument('--num-workers', default=4, type=int, help='Number of workers used in data-loading') 29 | parser.add_argument('--cuda', action='store_true', default=True, help='enable the gpu' ) 30 | # logging options 31 | parser.add_argument('--save-folder', default='Results/', help='Location to save epoch models') 32 | args = parser.parse_args() 33 | 34 | 35 | if __name__ == '__main__': 36 | 37 | 38 | # load testing data 39 | print("\nLoading testing data...") 40 | test_dataset = AGNEWs(label_data_path=args.test_path, alphabet_path=args.alphabet_path) 41 | print("Transferring testing data to iterator...") 42 | test_loader = DataLoader(test_dataset, batch_size=args.batch_size, num_workers=args.num_workers, drop_last=True) 43 | 44 | _, num_class_test = test_dataset.get_class_weight() 45 | print('\nNumber of testing samples: '+str(test_dataset.__len__())) 46 | for i, c in enumerate(num_class_test): 47 | print("\tLabel {:d}:".format(i).ljust(15)+"{:d}".format(c).rjust(8)) 48 | 49 | args.num_features = len(test_dataset.alphabet) 50 | model = CharCNN(args) 51 | print("=> loading weights from '{}'".format(args.model_path)) 52 | assert os.path.isfile(args.model_path), "=> no checkpoint found at '{}'".format(args.model_path) 53 | checkpoint = torch.load(args.model_path) 54 | model.load_state_dict(checkpoint['state_dict']) 55 | 56 | # using GPU 57 | if args.cuda: 58 | model = torch.nn.DataParallel(model).cuda() 59 | 60 | model.eval() 61 | corrects, avg_loss, accumulated_loss, size = 0, 0, 0, 0 62 | predicates_all, target_all = [], [] 63 | print('\nTesting...') 64 | for i_batch, (data) in enumerate(test_loader): 65 | inputs, target = data 66 | target.sub_(1) 67 | size+=len(target) 68 | if args.cuda: 69 | inputs, target = inputs.cuda(), target.cuda() 70 | 71 | inputs = Variable(inputs, volatile=True) 72 | target = Variable(target) 73 | logit = model(inputs) 74 | predicates = torch.max(logit, 1)[1].view(target.size()).data 75 | accumulated_loss += F.nll_loss(logit, target, size_average=False).data[0] 76 | corrects += (torch.max(logit, 1)[1].view(target.size()).data == target.data).sum() 77 | predicates_all+=predicates.cpu().numpy().tolist() 78 | target_all+=target.data.cpu().numpy().tolist() 79 | 80 | avg_loss = accumulated_loss/size 81 | accuracy = 100.0 * corrects/size 82 | print('\rEvaluation - loss: {:.6f} acc: {:.3f}%({}/{}) '.format(avg_loss, 83 | accuracy, 84 | corrects, 85 | size)) 86 | print_f_score(predicates_all, target_all) -------------------------------------------------------------------------------- /train.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | from metric import print_f_score 3 | from data_loader import AGNEWs 4 | from model import CharCNN 5 | from torch.utils.data import DataLoader 6 | from torch.autograd import Variable 7 | import torch.nn.functional as F 8 | from torch import optim 9 | from torch import nn 10 | import argparse 11 | import datetime 12 | import errno 13 | import torch 14 | import sys 15 | import os 16 | 17 | parser = argparse.ArgumentParser(description='Character level CNN text classifier training') 18 | # data 19 | parser.add_argument('--train_path', metavar='DIR', 20 | help='path to training data csv [default: data/ag_news_csv/train.csv]', 21 | default='data/ag_news_csv/train.csv') 22 | parser.add_argument('--val_path', metavar='DIR', 23 | help='path to validation data csv [default: data/ag_news_csv/test.csv]', 24 | default='data/ag_news_csv/test.csv') 25 | # learning 26 | learn = parser.add_argument_group('Learning options') 27 | learn.add_argument('--lr', type=float, default=0.0001, help='initial learning rate [default: 0.0001]') 28 | learn.add_argument('--epochs', type=int, default=200, help='number of epochs for train [default: 200]') 29 | learn.add_argument('--batch_size', type=int, default=32, help='batch size for training [default: 64]') 30 | learn.add_argument('--max_norm', default=400, type=int, help='Norm cutoff to prevent explosion of gradients') 31 | learn.add_argument('--optimizer', default='Adam', help='Type of optimizer. SGD|Adam|ASGD are supported [default: Adam]') 32 | learn.add_argument('--class_weight', default=None, action='store_true', help='Weights should be a 1D Tensor assigning weight to each of the classes.') 33 | learn.add_argument('--dynamic_lr', action='store_true', default=False, help='Use dynamic learning schedule.') 34 | learn.add_argument('--milestones', nargs='+', type=int, default=[5,10,15], help=' List of epoch indices. Must be increasing. Default:[5,10,15]') 35 | learn.add_argument('--decay_factor', default=0.5, type=float, help='Decay factor for reducing learning rate [default: 0.5]') 36 | # model (text classifier) 37 | cnn = parser.add_argument_group('Model options') 38 | cnn.add_argument('--alphabet_path', default='alphabet.json', help='Contains all characters for prediction') 39 | cnn.add_argument('--l0', type=int, default=1014, help='maximum length of input sequence to CNNs [default: 1014]') 40 | cnn.add_argument('--shuffle', action='store_true', default=False, help='shuffle the data every epoch') 41 | cnn.add_argument('--dropout', type=float, default=0.5, help='the probability for dropout [default: 0.5]') 42 | cnn.add_argument('-kernel_num', type=int, default=100, help='number of each kind of kernel') 43 | cnn.add_argument('-kernel_sizes', type=str, default='3,4,5', help='comma-separated kernel size to use for convolution') 44 | # device 45 | device = parser.add_argument_group('Device options') 46 | device.add_argument('--num_workers', default=1, type=int, help='Number of workers used in data-loading') 47 | device.add_argument('--cuda', action='store_true', default=False, help='enable the gpu' ) 48 | # experiment options 49 | experiment = parser.add_argument_group('Experiment options') 50 | experiment.add_argument('--verbose', dest='verbose', action='store_true', default=False, help='Turn on progress tracking per iteration for debugging') 51 | experiment.add_argument('--continue_from', default='', help='Continue from checkpoint model') 52 | experiment.add_argument('--checkpoint', dest='checkpoint', default=True, action='store_true', help='Enables checkpoint saving of model') 53 | experiment.add_argument('--checkpoint_per_batch', default=10000, type=int, help='Save checkpoint per batch. 0 means never save [default: 10000]') 54 | experiment.add_argument('--save_folder', default='models_CharCNN', help='Location to save epoch models, training configurations and results.') 55 | experiment.add_argument('--log_config', default=True, action='store_true', help='Store experiment configuration') 56 | experiment.add_argument('--log_result', default=True, action='store_true', help='Store experiment result') 57 | experiment.add_argument('--log_interval', type=int, default=1, help='how many steps to wait before logging training status [default: 1]') 58 | experiment.add_argument('--val_interval', type=int, default=200, help='how many steps to wait before vaidation [default: 200]') 59 | experiment.add_argument('--save_interval', type=int, default=1, help='how many epochs to wait before saving [default:1]') 60 | 61 | 62 | def train(train_loader, dev_loader, model, args): 63 | 64 | # optimization scheme 65 | if args.optimizer == 'Adam': 66 | optimizer = optim.Adam(model.parameters(), lr = args.lr) 67 | elif args.optimizer == 'SGD': 68 | optimizer = optim.SGD(model.parameters(), lr = args.lr, momentum = 0.9) 69 | elif args.optimizer == 'ASGD': 70 | optimizer = optim.ASGD(model.parameters(), lr = args.lr) 71 | 72 | # continue training from checkpoint model 73 | if args.continue_from: 74 | print("=> loading checkpoint from '{}'".format(args.continue_from)) 75 | assert os.path.isfile(args.continue_from), "=> no checkpoint found at '{}'".format(args.continue_from) 76 | checkpoint = torch.load(args.continue_from) 77 | start_epoch = checkpoint['epoch'] 78 | start_iter = checkpoint.get('iter', None) 79 | best_acc = checkpoint.get('best_acc', None) 80 | if start_iter is None: 81 | start_epoch += 1 # Assume that we saved a model after an epoch finished, so start at the next epoch. 82 | start_iter = 1 83 | else: 84 | start_iter += 1 85 | model.load_state_dict(checkpoint['state_dict']) 86 | optimizer.load_state_dict(checkpoint['optimizer']) 87 | else: 88 | start_epoch = 1 89 | start_iter = 1 90 | best_acc = None 91 | 92 | # dynamic learning scheme 93 | if args.dynamic_lr and args.optimizer != 'Adam': 94 | scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=args.milestones, gamma=args.decay_factor, last_epoch=-1) 95 | # scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer, factor=0.5, patience=10, threshold=1e-3) 96 | 97 | # multi-gpu 98 | if args.cuda: 99 | model = torch.nn.DataParallel(model).cuda() 100 | # model = model.cuda() 101 | 102 | model.train() 103 | 104 | for epoch in range(start_epoch, args.epochs+1): 105 | if args.dynamic_lr and args.optimizer != 'Adam': 106 | scheduler.step() 107 | for i_batch, data in enumerate(train_loader, start=start_iter): 108 | inputs, target = data 109 | target.sub_(1) 110 | 111 | if args.cuda: 112 | inputs, target = inputs.cuda(), target.cuda() 113 | 114 | inputs = Variable(inputs) 115 | target = Variable(target) 116 | logit = model(inputs) 117 | loss = F.nll_loss(logit, target) 118 | optimizer.zero_grad() 119 | loss.backward() 120 | torch.nn.utils.clip_grad_norm(model.parameters(), args.max_norm) 121 | optimizer.step() 122 | 123 | if args.cuda: 124 | torch.cuda.synchronize() 125 | 126 | if args.verbose: 127 | print('\nTargets, Predicates') 128 | print(torch.cat((target.unsqueeze(1), torch.unsqueeze(torch.max(logit, 1)[1].view(target.size()).data, 1)), 1)) 129 | print('\nLogit') 130 | print(logit) 131 | 132 | if i_batch % args.log_interval == 0: 133 | corrects = (torch.max(logit, 1)[1].view(target.size()).data == target.data).sum() 134 | accuracy = 100.0 * corrects/args.batch_size 135 | print('Epoch[{}] Batch[{}] - loss: {:.6f} lr: {:.5f} acc: {:.3f}% ({}/{})'.format(epoch, 136 | i_batch, 137 | loss.data, 138 | optimizer.state_dict()['param_groups'][0]['lr'], 139 | accuracy, 140 | corrects, 141 | args.batch_size)) 142 | if i_batch % args.val_interval == 0: 143 | 144 | val_loss, val_acc = eval(dev_loader, model, epoch, i_batch, optimizer, args) 145 | 146 | i_batch += 1 147 | if args.checkpoint and epoch % args.save_interval == 0: 148 | file_path = '%s/CharCNN_epoch_%d.pth.tar' % (args.save_folder, epoch) 149 | print("\r=> saving checkpoint model to %s" % file_path) 150 | save_checkpoint(model, {'epoch': epoch, 151 | 'optimizer' : optimizer.state_dict(), 152 | 'best_acc': best_acc}, 153 | file_path) 154 | 155 | # validation 156 | val_loss, val_acc = eval(dev_loader, model, epoch, i_batch, optimizer, args) 157 | # save best validation epoch model 158 | if best_acc is None or val_acc > best_acc: 159 | file_path = '%s/CharCNN_best.pth.tar' % (args.save_folder) 160 | print("\r=> found better validated model, saving to %s" % file_path) 161 | save_checkpoint(model, 162 | {'epoch': epoch, 163 | 'optimizer' : optimizer.state_dict(), 164 | 'best_acc': best_acc}, 165 | file_path) 166 | best_acc = val_acc 167 | print('\n') 168 | 169 | def eval(data_loader, model, epoch_train, batch_train, optimizer, args): 170 | model.eval() 171 | corrects, avg_loss, accumulated_loss, size = 0, 0, 0, 0 172 | predicates_all, target_all = [], [] 173 | for i_batch, (data) in enumerate(data_loader): 174 | inputs, target = data 175 | target.sub_(1) 176 | 177 | size += len(target) 178 | if args.cuda: 179 | inputs, target = inputs.cuda(), target.cuda() 180 | 181 | inputs = Variable(inputs, volatile=True) 182 | target = Variable(target) 183 | logit = model(inputs) 184 | predicates = torch.max(logit, 1)[1].view(target.size()).data 185 | accumulated_loss += F.nll_loss(logit, target, size_average = False).data 186 | corrects += (torch.max(logit, 1)[1].view(target.size()).data == target.data).sum() 187 | predicates_all += predicates.cpu().numpy().tolist() 188 | target_all += target.data.cpu().numpy().tolist() 189 | if args.cuda: 190 | torch.cuda.synchronize() 191 | 192 | avg_loss = accumulated_loss / size 193 | accuracy = 100.0 * corrects / size 194 | model.train() 195 | print('\nEvaluation - loss: {:.6f} lr: {:.5f} acc: {:.3f}% ({}/{}) '.format(avg_loss, 196 | optimizer.state_dict()['param_groups'][0]['lr'], 197 | accuracy, 198 | corrects, 199 | size)) 200 | print_f_score(predicates_all, target_all) 201 | print('\n') 202 | if args.log_result: 203 | with open(os.path.join(args.save_folder,'result.csv'), 'a') as r: 204 | r.write('\n{:d},{:d},{:.5f},{:.2f},{:f}'.format(epoch_train, 205 | batch_train, 206 | avg_loss, 207 | accuracy, 208 | optimizer.state_dict()['param_groups'][0]['lr'])) 209 | 210 | return avg_loss, accuracy 211 | 212 | def save_checkpoint(model, state, filename): 213 | model_is_cuda = next(model.parameters()).is_cuda 214 | model = model.module if model_is_cuda else model 215 | state['state_dict'] = model.state_dict() 216 | torch.save(state,filename) 217 | 218 | 219 | def make_data_loader(dataset_path, alphabet_path, l0, batch_size, num_workers): 220 | print("\nLoading data from {}".format(dataset_path)) 221 | dataset = AGNEWs(label_data_path=dataset_path, alphabet_path=alphabet_path, l0=l0) 222 | dataset_loader = DataLoader(dataset, batch_size=batch_size, num_workers=num_workers, drop_last=True, shuffle=True) 223 | return dataset, dataset_loader 224 | 225 | 226 | def main(): 227 | # parse arguments 228 | args = parser.parse_args() 229 | 230 | # load train and dev data 231 | train_dataset, train_loader = make_data_loader(args.train_path, 232 | args.alphabet_path, args.l0, args.batch_size, args.num_workers) 233 | dev_dataset, dev_loader = make_data_loader(args.val_path, 234 | args.alphabet_path, args.l0, args.batch_size, args.num_workers) 235 | 236 | # feature length 237 | args.num_features = len(train_dataset.alphabet) 238 | 239 | # get class weights 240 | class_weight, num_class_train = train_dataset.getClassWeight() 241 | _, num_class_dev = dev_dataset.getClassWeight() 242 | 243 | # when you have an unbalanced training set 244 | if args.class_weight != None: 245 | args.class_weight = torch.FloatTensor(class_weight).sqrt_() 246 | if args.cuda: 247 | args.class_weight = args.class_weight.cuda() 248 | 249 | print('\nNumber of training samples: {}'.format(str(train_dataset.__len__()))) 250 | for i, c in enumerate(num_class_train): 251 | print("\tLabel {:d}:".format(i).ljust(15)+"{:d}".format(c).rjust(8)) 252 | print('\nNumber of developing samples: {}'.format(str(dev_dataset.__len__()))) 253 | for i, c in enumerate(num_class_dev): 254 | print("\tLabel {:d}:".format(i).ljust(15)+"{:d}".format(c).rjust(8)) 255 | 256 | 257 | # make save folder 258 | try: 259 | os.makedirs(args.save_folder) 260 | except OSError as e: 261 | if e.errno == errno.EEXIST: 262 | print('Directory already exists.') 263 | else: 264 | raise 265 | # args.save_folder = os.path.join(args.save_folder, datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')) 266 | 267 | # configuration 268 | print("\nConfiguration:") 269 | for attr, value in sorted(args.__dict__.items()): 270 | print("\t{}:".format(attr.capitalize().replace('_', ' ')).ljust(25)+"{}".format(value)) 271 | 272 | # log result 273 | if args.log_result: 274 | with open(os.path.join(args.save_folder,'result.csv'), 'w') as r: 275 | r.write('{:s},{:s},{:s},{:s},{:s}'.format('epoch', 'batch', 'loss', 'acc', 'lr')) 276 | # model 277 | model = CharCNN(args) 278 | print(model) 279 | 280 | 281 | # train 282 | train(train_loader, dev_loader, model, args) 283 | 284 | if __name__ == '__main__': 285 | main() 286 | --------------------------------------------------------------------------------