├── .gitignore ├── README.md ├── custom_classifiers.py ├── data ├── binary │ ├── baroni2012.tsv │ ├── bless2011.tsv │ ├── kotlerman2010.tsv │ ├── levy2014.tsv │ └── turney2014.tsv └── multi │ ├── bless.txt │ ├── eval.txt │ ├── knh.txt │ └── root9.txt ├── fold.py ├── lexent.py ├── models.py ├── nn.py └── scripts ├── collect.py ├── filterspace.py ├── generategraphs.R ├── sigtest.py └── svdspace.py /.gitignore: -------------------------------------------------------------------------------- 1 | *.pyc 2 | Rplots.pdf 3 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | Hi, 2 | 3 | Thank you for showing interest in this. This code is not *quite* up to date. If 4 | you're interested in either the resource or the code, please email me 5 | and I'll make sure this gets posted immediately. 6 | 7 | Thank you, 8 | Stephen Roller 9 | -------------------------------------------------------------------------------- /custom_classifiers.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import numpy as np 4 | 5 | from sklearn.base import BaseEstimator, ClassifierMixin 6 | from sklearn.metrics import precision_recall_curve 7 | import sklearn.svm 8 | import sklearn.linear_model 9 | from sklearn.preprocessing import normalize 10 | 11 | class SuperTreeClassifier(BaseEstimator, ClassifierMixin): 12 | def __init__(self, n_features=4, proj=True, cos=True, incl=True): 13 | self.models = [] 14 | self.linear = sklearn.linear_model.LogisticRegression(penalty='l2', solver='liblinear', class_weight='balanced') 15 | self.n_features = n_features 16 | self.proj = proj 17 | self.cos = cos 18 | self.incl = incl 19 | #self.final = sklearn.svm.SVC(kernel='rbf', class_weight='balanced', max_iter=2000) 20 | self.final = sklearn.linear_model.LogisticRegression(penalty='l2', solver='liblinear', class_weight='balanced') 21 | 22 | def _rejection(self, plane, X): 23 | plane = plane / np.sqrt(plane.dot(plane)) 24 | D = X.shape[1] 25 | cos = np.sum(np.multiply(X, X), axis=1) 26 | proj = X.dot(plane) 27 | rejection = normalize(X - np.outer(proj, plane)) 28 | return proj, rejection 29 | 30 | def _subproj(self, plane, X): 31 | D = X.shape[1] / 2 32 | cos = np.sum(np.multiply(X[:,:D], X[:,D:]), axis=1) 33 | proj1, X1 = self._rejection(plane, X[:,:D]) 34 | proj2, X2 = self._rejection(plane, X[:,D:]) 35 | Xn = np.concatenate([X1, X2], axis=1) 36 | 37 | #return np.array([cos, proj1, proj2]), Xn # this one's pretty good 38 | features = [] 39 | if self.proj: 40 | features += [proj1, proj2] 41 | if self.cos: 42 | features += [cos] 43 | if self.incl: 44 | features += [proj2 - proj1] 45 | return np.array(features), Xn 46 | 47 | def fit(self, X, y): 48 | self.models = [] 49 | from sklearn.base import clone 50 | from sklearn.metrics import f1_score 51 | self.planes = [] 52 | extraction = [] 53 | for i in xrange(self.n_features): 54 | D = X.shape[1] / 2 55 | # copy it for feature extraction purposes 56 | self.linear.fit(X, y) 57 | self.models.append(clone(self.linear)) 58 | self.models[-1].coef_ = self.linear.coef_ 59 | 60 | lhs = self.linear.coef_[0,:D] 61 | rhs = self.linear.coef_[0,D:] 62 | if lhs.dot(lhs) > rhs.dot(rhs): 63 | hyperplane = lhs 64 | else: 65 | hyperplane = rhs 66 | feats, X = self._subproj(hyperplane, X) 67 | self.planes.append(hyperplane) 68 | hyperplane = hyperplane / np.sqrt(hyperplane.dot(hyperplane)) 69 | extraction.append(feats) 70 | 71 | self.coef_ = np.array(self.planes) 72 | Xe = np.concatenate(extraction).T 73 | self.final.fit(Xe, y) 74 | return self 75 | 76 | def predict(self, X): 77 | extraction = [] 78 | for p in self.planes: 79 | feats, X = self._subproj(p, X) 80 | extraction.append(feats) 81 | Xe = (np.concatenate(extraction).T) 82 | return self.final.predict(Xe) 83 | 84 | def set_params(self, **kwargs): 85 | for hp in ['n_features', 'proj', 'cos', 'incl']: 86 | if hp in kwargs: 87 | setattr(self, hp, kwargs[hp]) 88 | del kwargs[hp] 89 | self.final.set_params(**kwargs) 90 | 91 | class ThresholdClassifier(BaseEstimator, ClassifierMixin): 92 | def __init__(self): 93 | self.threshold_ = 0.0 94 | 95 | def fit(self, X, y): 96 | feature = X[:,0] 97 | p, r, t = precision_recall_curve(y, feature) 98 | #nonzero = (p > 0) & (r > 0) 99 | #p, r, t = p[nonzero], r[nonzero], t[nonzero[1:]] 100 | f1 = np.divide(2 * np.multiply(p, r), p + r) 101 | f1[np.isnan(f1)] = -1.0 102 | self.threshold_ = t[f1.argmax()] 103 | 104 | def predict(self, X): 105 | feature = X[:,0] 106 | return feature >= self.threshold_ 107 | 108 | def predict_proba(self, X): 109 | return np.concatenate([1-X, X], axis=1) 110 | 111 | def ksim_kernel(U, V): 112 | # kernel((ul, ur), (vl, vr)) = 113 | # (ul ur * vl vr) ^ (alpha / 2) * 114 | # (ul vl * ur vr) ^ (1 - alpha / 2) 115 | alpha = 0.5 116 | 117 | D = U.shape[1] / 2 118 | Ul, Ur = U[:,:D], U[:,D:] 119 | Vl, Vr = V[:,:D], V[:,D:] 120 | ulur = np.array([np.multiply(Ul, Ur).sum(axis=1)]).clip(0, 1e99) 121 | vlvr = np.array([np.multiply(Vl, Vr).sum(axis=1)]).clip(0, 1e99) 122 | ulvl = Ul.dot(Vl.T) 123 | urvr = Ur.dot(Vr.T) 124 | 125 | a = np.dot(ulur.T, vlvr) 126 | b = np.multiply(ulvl, urvr).clip(0, 1e99) 127 | 128 | a2 = np.power(a, alpha / 2.) 129 | b2 = np.power(b, 1 - alpha / 2.) 130 | 131 | retval = np.multiply(a2, b2) 132 | return retval 133 | 134 | -------------------------------------------------------------------------------- /data/binary/baroni2012.tsv: -------------------------------------------------------------------------------- 1 | word1 word2 label 2 | adjective document False 3 | adrenaline integer False 4 | adult anaesthetist False 5 | adult gent False 6 | adult instrument False 7 | adult librarian False 8 | adult nanny False 9 | adult physician False 10 | adult tree False 11 | advocate spokeswoman False 12 | affection organization False 13 | agony adult False 14 | agony anaesthetist False 15 | agony decoration False 16 | agreement rector False 17 | aircraft astronomy False 18 | aircraft biplane False 19 | aircraft bomber False 20 | aircraft insect False 21 | aircraft letter False 22 | aircrew playlist False 23 | airman sociology False 24 | airplane bomber False 25 | airplane chalet False 26 | alcohol container False 27 | alcohol hotel False 28 | alcohol liqueur False 29 | alcohol psychology False 30 | alga garment False 31 | algebra athlete False 32 | algebra potato False 33 | alloy bronze False 34 | ancestor motto False 35 | anger lizard False 36 | animal affidavit False 37 | animal artillery False 38 | animal bitterness False 39 | animal bug False 40 | animal bull False 41 | animal calf False 42 | animal cameraman False 43 | animal chick False 44 | 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vehicle False 934 | petroleum payment False 935 | pew glider False 936 | pharmacology man False 937 | phenomenon compensation False 938 | phenomenon fluorescence False 939 | phenomenon gale False 940 | phenomenon mishap False 941 | phenomenon polarization False 942 | phenomenon rain False 943 | phenomenon traction False 944 | physician shelter False 945 | physiology calculation False 946 | pig science False 947 | pilgrimage crew False 948 | piper illness False 949 | piracy feeling False 950 | pirate adult False 951 | pistol athlete False 952 | plant rector False 953 | platter publication False 954 | player batsman False 955 | player goalkeeper False 956 | player instrument False 957 | player physiotherapy False 958 | player quarterback False 959 | playlist bat False 960 | pocket vehicle False 961 | polarization emotion False 962 | policeman theft False 963 | polygon rectangle False 964 | polymer oil False 965 | polymerase treatment False 966 | porter panic False 967 | post rabbit False 968 | postgraduate water False 969 | potato foreman False 970 | pram greyhound False 971 | preamble meal False 972 | preconception laboratory False 973 | prefecture musician False 974 | priest pocket False 975 | priest secretariat False 976 | priory tycoon False 977 | procedure melon False 978 | produce music False 979 | produce raisin False 980 | professional anaesthetist False 981 | professional craftsman False 982 | professional liquor False 983 | professional ruler False 984 | professional surgeon False 985 | professional teacher False 986 | professorship misfortune False 987 | progenitor dad False 988 | progenitor father False 989 | progenitor mother False 990 | projectile limb False 991 | prosecutor magnitude False 992 | protein collagen False 993 | protein kilt False 994 | pseudonym dwelling False 995 | pseudonym golf False 996 | psychiatry clinician False 997 | psychoanalysis cow False 998 | psychotherapy dinner False 999 | publication bestseller False 1000 | publication linguist False 1001 | publication manual False 1002 | publication workbook False 1003 | pudding wind False 1004 | puppy employee False 1005 | puppy performer False 1006 | race dioxin False 1007 | radius fluid False 1008 | railway metro False 1009 | rain drizzle False 1010 | receptionist schoolmaster False 1011 | record autobiography False 1012 | record memo False 1013 | record spouse False 1014 | record wine False 1015 | red bird False 1016 | reelection ache False 1017 | reformer crime False 1018 | reggae rectangle False 1019 | reimbursement insect False 1020 | relative game False 1021 | relative granny False 1022 | relative infant False 1023 | relative leader False 1024 | relative musician False 1025 | relative ore False 1026 | relative parent False 1027 | relative son False 1028 | relief herb False 1029 | relief kidnapping False 1030 | remorse water False 1031 | representative alderman False 1032 | reptile business False 1033 | reptile list False 1034 | reptile record False 1035 | request ultimatum False 1036 | resentment employee False 1037 | resignation discipline False 1038 | revolver animal False 1039 | rifle psychoanalysis False 1040 | right kingfisher False 1041 | road freeway False 1042 | road highway False 1043 | road representative False 1044 | road roadway False 1045 | roast salmon False 1046 | rodent hamster False 1047 | rodent hedgehog False 1048 | rodent vole False 1049 | rodent weapon False 1050 | roofing recovery False 1051 | room classroom False 1052 | room sauna False 1053 | ruler algebra False 1054 | ruler pancreas False 1055 | sack apostle False 1056 | sack emotion False 1057 | sailor forearm False 1058 | sailor oil False 1059 | sailor privateer False 1060 | salesman ache False 1061 | salmon intestine False 1062 | sausage crew False 1063 | saying machine False 1064 | saying motto False 1065 | saying slogan False 1066 | scapegoat temperament False 1067 | school gymnasium False 1068 | science alga False 1069 | science algebra False 1070 | science artery False 1071 | science concept False 1072 | science decree False 1073 | science dentistry False 1074 | science employee False 1075 | science linguistics False 1076 | science math False 1077 | science neurology False 1078 | science neuroscience False 1079 | science oncology False 1080 | science pear False 1081 | science robin False 1082 | science wheat False 1083 | scientist dad False 1084 | scientist henchman False 1085 | scourge end False 1086 | seabird penguin False 1087 | seafood carp False 1088 | seafood herring False 1089 | seafood mackerel False 1090 | seafood worker False 1091 | seaplane crystal False 1092 | secretariat carbon False 1093 | section preamble False 1094 | security fresco False 1095 | security indemnity False 1096 | sedan tissue False 1097 | sensation fragrance False 1098 | sensation information False 1099 | sensation molecule False 1100 | sensation tool False 1101 | servant croquet False 1102 | serviceman soldier False 1103 | shark assortment False 1104 | shellfish emotion False 1105 | sherry cancer False 1106 | sherry rodent False 1107 | ship submarine False 1108 | ship tanker False 1109 | shirt thoroughfare False 1110 | shortcut decoration False 1111 | shortcut feeling False 1112 | shower bee False 1113 | shrine captivity False 1114 | signal walnut False 1115 | singer soprano False 1116 | sir opium False 1117 | site reptile False 1118 | sixty relative False 1119 | slalom barrier False 1120 | slalom hedgehog False 1121 | slogan mixture False 1122 | sloop rector False 1123 | snail bull False 1124 | snake chemical False 1125 | snake jewel False 1126 | snippet feeling False 1127 | soccer organization False 1128 | sociologist panda False 1129 | software food False 1130 | software fruit False 1131 | software parser False 1132 | solid ancestor False 1133 | solid ape False 1134 | solid cookie False 1135 | solid orange False 1136 | solid quartz False 1137 | solid shellfish False 1138 | solid wood False 1139 | solution batsman False 1140 | solution migration False 1141 | son hospital False 1142 | sonata symphony False 1143 | song piper False 1144 | spaghetti commodity False 1145 | spaghetti forearm False 1146 | spaghetti workman False 1147 | spoon immigration False 1148 | sport badminton False 1149 | sport equipment False 1150 | sport football False 1151 | sport garment False 1152 | sport golf False 1153 | sport histogram False 1154 | sport hymn False 1155 | sport racing False 1156 | sport swimming False 1157 | spouse commodity False 1158 | stag eagle False 1159 | stag virus False 1160 | stallion statement False 1161 | standing animal False 1162 | standing ape False 1163 | statement accusation False 1164 | statement contract False 1165 | statement ship False 1166 | statement spouse False 1167 | statesman buggy False 1168 | status baronetcy False 1169 | stocking bird False 1170 | stocking limousine False 1171 | storm overpayment False 1172 | storm sandwich False 1173 | storm solid False 1174 | storm typhoon False 1175 | strawberry alcohol False 1176 | subcommittee fresco False 1177 | subcontractor cassette False 1178 | sulphate hair False 1179 | sunlight dealer False 1180 | sunlight statement False 1181 | surface screen False 1182 | surprise guesthouse False 1183 | swan symbol False 1184 | swimming motel False 1185 | swine humankind False 1186 | symbol cairn False 1187 | symbol leaf False 1188 | symbol vehicle False 1189 | symptom spasm False 1190 | system military False 1191 | tank building False 1192 | tanker grandmother False 1193 | technician relative False 1194 | telecommunication crime False 1195 | telecommunication twenty False 1196 | temperament aristocrat False 1197 | term telly False 1198 | tern discipline False 1199 | terror granny False 1200 | text illustration False 1201 | text invitation False 1202 | theater value False 1203 | theatre brook False 1204 | theology greyhound False 1205 | theology phenomenon False 1206 | therapy building False 1207 | therapy machine False 1208 | therapy psychoanalysis False 1209 | therapy son False 1210 | thief housing False 1211 | thief potato False 1212 | thoroughfare alley False 1213 | thoroughfare boulevard False 1214 | thrill energy False 1215 | thunderstorm shower False 1216 | tissue animal False 1217 | tissue skin False 1218 | tissue solution False 1219 | toast antibiotic False 1220 | toddler lobster False 1221 | tomorrow relative False 1222 | tool celery False 1223 | tool fluid False 1224 | tool screwdriver False 1225 | tortoise joint False 1226 | tower aneurysm False 1227 | tower silo False 1228 | tower turret False 1229 | traction influenza False 1230 | trait competitiveness False 1231 | trait folly False 1232 | trait goose False 1233 | trait maker False 1234 | trait parameter False 1235 | trait road False 1236 | trait temperament False 1237 | transaction investing False 1238 | transformation conversion False 1239 | travel algebra False 1240 | travel safari False 1241 | traveler owl False 1242 | traveler performer False 1243 | treatment alcohol False 1244 | treatment people False 1245 | treatment psychoanalysis False 1246 | treatment radiotherapy False 1247 | tree almond False 1248 | tree holly False 1249 | tree mango False 1250 | tree mangrove False 1251 | tree travel False 1252 | trolley soloist False 1253 | trouser geometry False 1254 | tumor laborer False 1255 | tumor melanoma False 1256 | tumor mesothelioma False 1257 | tumor pasta False 1258 | tumor writer False 1259 | tumour luncheon False 1260 | turbine cold False 1261 | turkey employee False 1262 | typography surface False 1263 | underside sensation False 1264 | undertaking robin False 1265 | undertaking slalom False 1266 | underwear lingerie False 1267 | utensil kettle False 1268 | value teaching False 1269 | vegetable artiste False 1270 | vegetable cabbage False 1271 | vegetable vehicle False 1272 | vehicle amphibian False 1273 | vehicle auto False 1274 | vehicle bike False 1275 | vehicle duck False 1276 | vehicle elm False 1277 | vehicle entertainer False 1278 | vehicle frigate False 1279 | vehicle gunboat False 1280 | vehicle invertebrate False 1281 | vehicle milk False 1282 | vehicle osteoarthritis False 1283 | vehicle parser False 1284 | vehicle sedan False 1285 | vehicle sloop False 1286 | vehicle tank False 1287 | vehicle trolley False 1288 | vehicle tsunami False 1289 | vehicle vintage False 1290 | vehicle warship False 1291 | vehicle woman False 1292 | vehicle worker False 1293 | velocity potato False 1294 | velocity sociology False 1295 | vertebrate art False 1296 | vertebrate asp False 1297 | vertebrate bat False 1298 | vertebrate bear False 1299 | vertebrate bitterness False 1300 | vertebrate chariot False 1301 | vertebrate conservatism False 1302 | vertebrate corporation False 1303 | vertebrate cow False 1304 | vertebrate crystal False 1305 | vertebrate eagle False 1306 | vertebrate hedgehog False 1307 | vertebrate lion False 1308 | vertebrate mare False 1309 | vertebrate organization False 1310 | vertebrate panda False 1311 | vertebrate pheasant False 1312 | vertebrate puppy False 1313 | vertebrate raven False 1314 | vertebrate serpent False 1315 | vertebrate site False 1316 | vertebrate spear False 1317 | vertebrate victim False 1318 | vertebrate vole False 1319 | vertebrate woodpecker False 1320 | vertebrate worker False 1321 | vertebrate yellow False 1322 | vertex priest False 1323 | vessel stick False 1324 | vial commodity False 1325 | vicar bottle False 1326 | vicar shareholder False 1327 | vicar suit False 1328 | vodka privateer False 1329 | volleyball pc False 1330 | vulture fluid False 1331 | wader science False 1332 | wage airplane False 1333 | waiter waitress False 1334 | walk vehicle False 1335 | warbler father False 1336 | ware feeling False 1337 | ware fork False 1338 | ware shirt False 1339 | water seawater False 1340 | waterfowl crystal False 1341 | waterfowl parent False 1342 | wave tsunami False 1343 | weakening invertebrate False 1344 | weapon rifle False 1345 | wheat pain False 1346 | whiskey dagger False 1347 | whiskey meal False 1348 | whisky traveler False 1349 | wife beer False 1350 | wife coupe False 1351 | wind vicar False 1352 | windfall bird False 1353 | wine football False 1354 | wine road False 1355 | woman bridesmaid False 1356 | woman math False 1357 | woman mistress False 1358 | wood maple False 1359 | woodpecker covenant False 1360 | word emotion False 1361 | word flu False 1362 | word modifier False 1363 | word trait False 1364 | work bird False 1365 | worker airman False 1366 | worker athlete False 1367 | worker breaker False 1368 | worker cook False 1369 | worker editor False 1370 | worker furniture False 1371 | worker hospital False 1372 | worker phenomenon False 1373 | worker pilot False 1374 | worker postman False 1375 | worker traveler False 1376 | workman fruit False 1377 | workman porter False 1378 | workplace snippet False 1379 | workplace studio False 1380 | wrath science False 1381 | writer armchair False 1382 | writer dramatist False 1383 | writer poet False 1384 | yellow protein False 1385 | yesterday discipline False 1386 | yesterday subcommittee False 1387 | abstraction concept True 1388 | accusation statement True 1389 | ache pain True 1390 | acid chemical True 1391 | acoustics discipline True 1392 | adjective word True 1393 | adrenaline chemical True 1394 | adrenaline neurotransmitter True 1395 | aesthetic doctrine True 1396 | affection feeling True 1397 | affidavit document True 1398 | agony feeling True 1399 | aide serviceman True 1400 | aircraft vehicle True 1401 | aircrew crew True 1402 | airman worker True 1403 | airplane vehicle True 1404 | alcohol fluid True 1405 | alderman representative True 1406 | ale alcohol True 1407 | ale fluid True 1408 | alga microorganism True 1409 | algebra mathematics True 1410 | algebra science True 1411 | alley thoroughfare True 1412 | almond tree True 1413 | alpha symbol True 1414 | ambassador diplomat True 1415 | ambassador worker True 1416 | amphetamine drug True 1417 | amphibian vehicle True 1418 | anaesthetic drug True 1419 | anaesthetist adult True 1420 | anaesthetist professional True 1421 | analogy inference True 1422 | anatomy discipline True 1423 | aneurysm disorder True 1424 | anger emotion True 1425 | anger feeling True 1426 | animosity emotion True 1427 | animosity feeling True 1428 | annals periodical True 1429 | anorexia disorder True 1430 | answer statement True 1431 | ant insect True 1432 | ant invertebrate True 1433 | antibiotic drug True 1434 | antibody molecule True 1435 | antiquity era True 1436 | apathy feeling True 1437 | ape animal True 1438 | ape mammal True 1439 | aphid insect True 1440 | aphid invertebrate True 1441 | apostle believer True 1442 | apple solid True 1443 | apprehension fear True 1444 | aquarium container True 1445 | aqueduct conduit True 1446 | archbishop clergyman True 1447 | archbishop priest True 1448 | arithmetic discipline True 1449 | armchair chair True 1450 | army organization True 1451 | aromatherapy therapy True 1452 | artery vessel True 1453 | artillery armament True 1454 | artiste entertainer True 1455 | artiste performer True 1456 | asp reptile True 1457 | asp snake True 1458 | asp vertebrate True 1459 | aspirin drug True 1460 | association organization True 1461 | assortment collection True 1462 | asthma illness True 1463 | astronomy science True 1464 | asylum shelter True 1465 | attorney professional True 1466 | attraction phenomenon True 1467 | auto vehicle True 1468 | autobiography record True 1469 | automobile vehicle True 1470 | baby offspring True 1471 | bacterium microorganism True 1472 | badminton sport True 1473 | baggage container True 1474 | bailiff worker True 1475 | balloon aircraft True 1476 | bamboo wood True 1477 | ban decree True 1478 | bargain agreement True 1479 | baritone entertainer True 1480 | baritone singer True 1481 | baroness aristocrat True 1482 | baronetcy status True 1483 | barrier obstruction True 1484 | basket container True 1485 | basketball game True 1486 | bassist entertainer True 1487 | bassist musician True 1488 | bat vertebrate True 1489 | batsman athlete True 1490 | batsman player True 1491 | battleship ship True 1492 | battleship vehicle True 1493 | bead jewelry True 1494 | bean vegetable True 1495 | bear carnivore True 1496 | bear mammal True 1497 | bear vertebrate True 1498 | beard hair True 1499 | bed furniture True 1500 | bee animal True 1501 | bee invertebrate True 1502 | beech tree True 1503 | beer beverage True 1504 | beer liquid True 1505 | bend curve True 1506 | benzene chemical True 1507 | benzene hydrocarbon True 1508 | benzodiazepine drug True 1509 | bereavement emotion True 1510 | berry solid True 1511 | bestseller publication True 1512 | beverage fluid True 1513 | beverage liquid True 1514 | bib fabric True 1515 | bike vehicle True 1516 | binder machine True 1517 | bingo game True 1518 | biochemistry chemistry True 1519 | biochemistry science True 1520 | biologist scientist True 1521 | biotechnology discipline True 1522 | biplane aircraft True 1523 | biplane airplane True 1524 | biplane vehicle True 1525 | bird animal True 1526 | birthday anniversary True 1527 | bitterness emotion True 1528 | bitterness feeling True 1529 | black color True 1530 | blaze combustion True 1531 | bluegrass herb True 1532 | boar mammal True 1533 | bomber aircraft True 1534 | bomber airplane True 1535 | bonnet clothing True 1536 | bonnet commodity True 1537 | bookmark marker True 1538 | bookshop shop True 1539 | booze beverage True 1540 | booze drug True 1541 | border boundary True 1542 | boss leader True 1543 | bottle container True 1544 | boulevard thoroughfare True 1545 | bounty payment True 1546 | bourgeoisie people True 1547 | bowling game True 1548 | box container True 1549 | bra clothing True 1550 | breaker worker True 1551 | breeze wind True 1552 | brethren organization True 1553 | bridesmaid woman True 1554 | brigade organization True 1555 | bronze alloy True 1556 | brook stream True 1557 | brother kinsman True 1558 | buffalo mammal True 1559 | bug animal True 1560 | bug invertebrate True 1561 | buggy container True 1562 | buggy vehicle True 1563 | bull animal True 1564 | bull mammal True 1565 | bulldog dog True 1566 | bungalow house True 1567 | bungalow housing True 1568 | bureau organization True 1569 | butcher merchant True 1570 | butter solid True 1571 | butterfly animal True 1572 | butterfly insect True 1573 | cabbage vegetable True 1574 | cafe restaurant True 1575 | cage enclosure True 1576 | cairn symbol True 1577 | calamity misfortune True 1578 | calculation procedure True 1579 | calf animal True 1580 | camera equipment True 1581 | cameraman artist True 1582 | campsite site True 1583 | candy food True 1584 | cannon armament True 1585 | cannon artillery True 1586 | carbohydrate molecule True 1587 | carbonate chemical True 1588 | carcinoma cancer True 1589 | carcinoma tumor True 1590 | cardinal bishop True 1591 | cardinal leader True 1592 | caring love True 1593 | carnage murder True 1594 | carp seafood True 1595 | carpenter worker True 1596 | casket container True 1597 | cassette container True 1598 | castle building True 1599 | castle dwelling True 1600 | castle house True 1601 | castle housing True 1602 | cat carnivore True 1603 | cat mammal True 1604 | cataract illness True 1605 | catastrophe misfortune True 1606 | catcher player True 1607 | caterpillar larva True 1608 | caucus gathering True 1609 | celery herb True 1610 | cellist entertainer True 1611 | cellist performer True 1612 | cellulose carbohydrate True 1613 | cellulose chemical True 1614 | cemetery site True 1615 | cereal herb True 1616 | chalet building True 1617 | chalet house True 1618 | chamber enclosure True 1619 | champagne alcohol True 1620 | champagne wine True 1621 | chancellor leader True 1622 | chant music True 1623 | chapel building True 1624 | charcoal carbon True 1625 | chariot vehicle True 1626 | charity institution True 1627 | chateau dwelling True 1628 | checklist information True 1629 | checklist list True 1630 | cheese food True 1631 | chef worker True 1632 | chemistry science True 1633 | chemotherapy care True 1634 | chick animal True 1635 | chick bird True 1636 | chick vertebrate True 1637 | chicken solid True 1638 | chilli vegetable True 1639 | chimpanzee mammal True 1640 | chimpanzee vertebrate True 1641 | chocolate food True 1642 | church organization True 1643 | cider fluid True 1644 | cipher message True 1645 | classroom room True 1646 | clerk worker True 1647 | clinician professional True 1648 | clown fool True 1649 | club organization True 1650 | clubhouse building True 1651 | coach trainer True 1652 | coaching occupation True 1653 | cockroach insect True 1654 | cockroach invertebrate True 1655 | cocktail alcohol True 1656 | cold illness True 1657 | collagen molecule True 1658 | collagen protein True 1659 | colon organ True 1660 | colt male True 1661 | columnist journalist True 1662 | comedian performer True 1663 | comic entertainer True 1664 | comic performer True 1665 | comment statement True 1666 | commission organization True 1667 | committee organization True 1668 | company institution True 1669 | company organization True 1670 | compass instrument True 1671 | compassion feeling True 1672 | competitiveness trait True 1673 | complacency feeling True 1674 | compost mixture True 1675 | concert performance True 1676 | concerto music True 1677 | condom contraceptive True 1678 | condominium dwelling True 1679 | condominium housing True 1680 | conjecture idea True 1681 | conservatism attitude True 1682 | contract statement True 1683 | convent building True 1684 | convent dwelling True 1685 | convention meeting True 1686 | conversion transformation True 1687 | cook worker True 1688 | cookbook book True 1689 | cookie solid True 1690 | cool temperature True 1691 | copyright right True 1692 | coriander herb True 1693 | corporation organization True 1694 | corridor passageway True 1695 | cosmology discipline True 1696 | cottage house True 1697 | cottage housing True 1698 | cotton fiber True 1699 | council organization True 1700 | counterattack attack True 1701 | country organization True 1702 | coupe vehicle True 1703 | courthouse building True 1704 | courtroom room True 1705 | covenant document True 1706 | cow vertebrate True 1707 | cowboy workman True 1708 | crab invertebrate True 1709 | cracker food True 1710 | cradle furniture True 1711 | craftsman professional True 1712 | cricket insect True 1713 | cricketer athlete True 1714 | criminology discipline True 1715 | crocodile animal True 1716 | croquet game True 1717 | croquet sport True 1718 | crow animal True 1719 | crusade undertaking True 1720 | cutlery tool True 1721 | cycling sport True 1722 | cynicism feeling True 1723 | dad progenitor True 1724 | dad relative True 1725 | daddy parent True 1726 | dagger instrument True 1727 | dance art True 1728 | dancer entertainer True 1729 | dancing discipline True 1730 | dart projectile True 1731 | daughter offspring True 1732 | deafness disability True 1733 | dealer merchant True 1734 | dealership business True 1735 | dean leader True 1736 | deanery building True 1737 | deanery dwelling True 1738 | deanery house True 1739 | declaration statement True 1740 | decrease change True 1741 | deer animal True 1742 | deer mammal True 1743 | dementia insanity True 1744 | denim clothing True 1745 | dentistry medicine True 1746 | dentistry science True 1747 | department organization True 1748 | depth magnitude True 1749 | dermatitis disease True 1750 | descendent relative True 1751 | desire feeling True 1752 | desk furniture True 1753 | detective policeman True 1754 | diabetes disease True 1755 | dictionary book True 1756 | dinghy boat True 1757 | dinner meal True 1758 | dinosaur vertebrate True 1759 | dioxide oxide True 1760 | dioxin hydrocarbon True 1761 | diplomat worker True 1762 | directorate organization True 1763 | disappointment feeling True 1764 | disco music True 1765 | discussion communication True 1766 | dish container True 1767 | dispenser container True 1768 | displeasure emotion True 1769 | documentary movie True 1770 | documentation information True 1771 | dog carnivore True 1772 | dog mammal True 1773 | dogma doctrine True 1774 | dolphin animal True 1775 | dorm housing True 1776 | dormitory building True 1777 | dove animal True 1778 | draft document True 1779 | dragonfly animal True 1780 | dragonfly insect True 1781 | dramatist writer True 1782 | drift phenomenon True 1783 | drinker consumer True 1784 | drizzle rain True 1785 | drone insect True 1786 | drummer entertainer True 1787 | drummer performer True 1788 | dryer commodity True 1789 | duck bird True 1790 | dustbin bin True 1791 | dwelling housing True 1792 | dyke lesbian True 1793 | dynamite explosive True 1794 | eagle animal True 1795 | eagle bird True 1796 | eagle vertebrate True 1797 | earring decoration True 1798 | eatery building True 1799 | eating consumption True 1800 | ecologist scientist True 1801 | economics discipline True 1802 | economist scientist True 1803 | ecstasy emotion True 1804 | ecstasy feeling True 1805 | edge boundary True 1806 | editor worker True 1807 | editorial prose True 1808 | educator professional True 1809 | eel solid True 1810 | electrician worker True 1811 | electrolyte solution True 1812 | electronics discipline True 1813 | electronics science True 1814 | elephant animal True 1815 | eleven integer True 1816 | elite people True 1817 | elm tree True 1818 | emigrant migrant True 1819 | emigration migration True 1820 | employee worker True 1821 | empress ruler True 1822 | encyclopedia book True 1823 | endurance strength True 1824 | engineering occupation True 1825 | enumeration information True 1826 | enumeration list True 1827 | environmentalist reformer True 1828 | envy feeling True 1829 | enzyme molecule True 1830 | enzymology biochemistry True 1831 | enzymology science True 1832 | epic poem True 1833 | epistle letter True 1834 | etching art True 1835 | excitement feeling True 1836 | excuse explanation True 1837 | experiment research True 1838 | facade surface True 1839 | fairytale narrative True 1840 | fallacy idea True 1841 | falsehood statement True 1842 | farmhouse building True 1843 | farmhouse house True 1844 | father progenitor True 1845 | feeder animal True 1846 | felony transgression True 1847 | fence barrier True 1848 | fencing obstruction True 1849 | fender barrier True 1850 | ferret carnivore True 1851 | ferry boat True 1852 | ferry vehicle True 1853 | fielder athlete True 1854 | fillet meat True 1855 | filly female True 1856 | final contest True 1857 | fingertip tip True 1858 | firearm weapon True 1859 | firm business True 1860 | firm organization True 1861 | fish animal True 1862 | fisherman worker True 1863 | fishing sport True 1864 | flea invertebrate True 1865 | flea parasite True 1866 | floor surface True 1867 | flour food True 1868 | flu disease True 1869 | fluorescence phenomenon True 1870 | fly invertebrate True 1871 | fodder worker True 1872 | foetus vertebrate True 1873 | folly trait True 1874 | football game True 1875 | football sport True 1876 | footbridge bridge True 1877 | forearm limb True 1878 | foreman superior True 1879 | fork ware True 1880 | foundry plant True 1881 | fourteen integer True 1882 | fox animal True 1883 | fox mammal True 1884 | fox vertebrate True 1885 | fragrance sensation True 1886 | freeware software True 1887 | freeway road True 1888 | fresco art True 1889 | fresco painting True 1890 | frigate vehicle True 1891 | fright emotion True 1892 | frustration feeling True 1893 | fullback athlete True 1894 | funeral ceremony True 1895 | gale phenomenon True 1896 | gall disease True 1897 | galley vehicle True 1898 | gas phenomenon True 1899 | gasoline fuel True 1900 | gasoline hydrocarbon True 1901 | gastropod invertebrate True 1902 | gate barrier True 1903 | gateway entrance True 1904 | gauge instrument True 1905 | geek performer True 1906 | gemstone crystal True 1907 | generator apparatus True 1908 | gent adult True 1909 | gentry people True 1910 | geology discipline True 1911 | geometry discipline True 1912 | geometry science True 1913 | gin beverage True 1914 | ginger herb True 1915 | girlfriend woman True 1916 | gladiator combatant True 1917 | gland organ True 1918 | glaucoma disease True 1919 | glider aircraft True 1920 | glider vehicle True 1921 | goalkeeper athlete True 1922 | goalkeeper player True 1923 | goat mammal True 1924 | goldfish vertebrate True 1925 | golf sport True 1926 | golfer player True 1927 | goose vertebrate True 1928 | goose waterfowl True 1929 | gorge valley True 1930 | gorilla mammal True 1931 | governor politician True 1932 | gown clothing True 1933 | graft tissue True 1934 | grandchild offspring True 1935 | grandchild relative True 1936 | granddaughter offspring True 1937 | grandfather grandparent True 1938 | grandmother grandparent True 1939 | grandmother relative True 1940 | granny relative True 1941 | graveyard site True 1942 | green color True 1943 | greyhound animal True 1944 | greyhound dog True 1945 | greyhound hound True 1946 | grove vegetation True 1947 | guesthouse housing True 1948 | gunboat boat True 1949 | gunboat vehicle True 1950 | gunner serviceman True 1951 | gym facility True 1952 | gymnasium school True 1953 | hall passageway True 1954 | hallway passageway True 1955 | hamlet community True 1956 | hamster rodent True 1957 | handgun gun True 1958 | handgun instrument True 1959 | handgun weapon True 1960 | handset equipment True 1961 | hardness consistency True 1962 | hare animal True 1963 | hare mammal True 1964 | hawk animal True 1965 | hawk bird True 1966 | headline text True 1967 | heat energy True 1968 | hedgehog rodent True 1969 | hedgehog vertebrate True 1970 | height dimension True 1971 | height magnitude True 1972 | helicopter vehicle True 1973 | hen bird True 1974 | henchman criminal True 1975 | hepatitis illness True 1976 | heroism trait True 1977 | herpes disease True 1978 | herring seafood True 1979 | heterogeneity difference True 1980 | highway road True 1981 | histogram chart True 1982 | hockey sport True 1983 | holly tree True 1984 | honey food True 1985 | horse animal True 1986 | horse mammal True 1987 | horse vertebrate True 1988 | horseman rider True 1989 | hose commodity True 1990 | hospital building True 1991 | hostel hotel True 1992 | hostess host True 1993 | house building True 1994 | housekeeper servant True 1995 | housewife woman True 1996 | human vertebrate True 1997 | humanism doctrine True 1998 | humanist scholar True 1999 | humankind vertebrate True 2000 | hurricane storm True 2001 | husband relative True 2002 | hymn song True 2003 | hypnotherapy therapy True 2004 | hypnotherapy treatment True 2005 | hysteria disorder True 2006 | ice crystal True 2007 | icon signal True 2008 | illustration artwork True 2009 | immigration migration True 2010 | immunology discipline True 2011 | immunology science True 2012 | importation commerce True 2013 | indemnity security True 2014 | infant relative True 2015 | influenza illness True 2016 | infusion solution True 2017 | initiation ceremony True 2018 | ink fluid True 2019 | ink liquid True 2020 | inn building True 2021 | insect animal True 2022 | insecticide pesticide True 2023 | insomnia disorder True 2024 | internment captivity True 2025 | interoperability ability True 2026 | intestine organ True 2027 | intranet system True 2028 | invertebrate animal True 2029 | investing transaction True 2030 | investment transaction True 2031 | invitation text True 2032 | ipod system True 2033 | islander inhabitant True 2034 | iv digit True 2035 | ix digit True 2036 | jacket garment True 2037 | jam food True 2038 | jealousy feeling True 2039 | jean garment True 2040 | jelly food True 2041 | jet vehicle True 2042 | jeweller maker True 2043 | jewelry decoration True 2044 | jigsaw machine True 2045 | jigsaw tool True 2046 | joker entertainer True 2047 | joker performer True 2048 | jurisprudence discipline True 2049 | kangaroo animal True 2050 | kangaroo mammal True 2051 | karaoke entertainment True 2052 | kestrel animal True 2053 | kestrel falcon True 2054 | kestrel hawk True 2055 | kestrel vertebrate True 2056 | kettle container True 2057 | kettle utensil True 2058 | keyboardist performer True 2059 | kickoff kick True 2060 | kidnapping crime True 2061 | kilt clothing True 2062 | kilt commodity True 2063 | kindergarten institution True 2064 | kindergarten organization True 2065 | kingfisher bird True 2066 | kingfisher vertebrate True 2067 | kinsman relative True 2068 | knee joint True 2069 | knife tool True 2070 | knuckle joint True 2071 | laboratory workplace True 2072 | laborer worker True 2073 | lactose chemical True 2074 | lactose molecule True 2075 | lady adult True 2076 | lamb animal True 2077 | laptop computer True 2078 | laptop machine True 2079 | leak opening True 2080 | lecturer adult True 2081 | leg limb True 2082 | lemon fruit True 2083 | leprosy disease True 2084 | leprosy illness True 2085 | leukaemia cancer True 2086 | leukaemia disease True 2087 | leukaemia tumor True 2088 | leukemia tumor True 2089 | librarian adult True 2090 | license document True 2091 | limousine car True 2092 | limousine vehicle True 2093 | lingerie clothing True 2094 | lingerie garment True 2095 | lingerie underwear True 2096 | linguist scientist True 2097 | linguistics science True 2098 | lion animal True 2099 | lion vertebrate True 2100 | lipid molecule True 2101 | liqueur alcohol True 2102 | liqueur beverage True 2103 | liqueur fluid True 2104 | liquor beverage True 2105 | liquor fluid True 2106 | liquor liquid True 2107 | lizard reptile True 2108 | lobster seafood True 2109 | locomotive vehicle True 2110 | logic discipline True 2111 | logo signal True 2112 | logo symbol True 2113 | longing feeling True 2114 | loo room True 2115 | louse insect True 2116 | love feeling True 2117 | lunch meal True 2118 | luncheon meal True 2119 | lupus disease True 2120 | lymphoma tumor True 2121 | mackerel seafood True 2122 | magazine medium True 2123 | maggot animal True 2124 | maggot larva True 2125 | magistrate official True 2126 | magpie animal True 2127 | magpie bird True 2128 | maid servant True 2129 | mail message True 2130 | mailbox container True 2131 | maize herb True 2132 | malaria infection True 2133 | man adult True 2134 | mango tree True 2135 | mangrove tree True 2136 | mankind mammal True 2137 | manor housing True 2138 | manual book True 2139 | manual publication True 2140 | maple wood True 2141 | mare animal True 2142 | mare horse True 2143 | mare vertebrate True 2144 | margarine food True 2145 | mariner worker True 2146 | marquee tent True 2147 | massage treatment True 2148 | mater ancestor True 2149 | math science True 2150 | measles illness True 2151 | medication drug True 2152 | medicine discipline True 2153 | melanoma cancer True 2154 | melanoma carcinoma True 2155 | melanoma tumor True 2156 | melon fruit True 2157 | melon solid True 2158 | memo note True 2159 | memo record True 2160 | memorandum note True 2161 | meningitis illness True 2162 | mesothelioma cancer True 2163 | mesothelioma disease True 2164 | mesothelioma illness True 2165 | mesothelioma tumor True 2166 | metro railway True 2167 | microbiology biology True 2168 | midwife professional True 2169 | migraine ache True 2170 | migrant traveler True 2171 | military organization True 2172 | militia organization True 2173 | milk beverage True 2174 | milk fluid True 2175 | milk food True 2176 | milk liquid True 2177 | mime performer True 2178 | miner workman True 2179 | mishap phenomenon True 2180 | missile instrument True 2181 | missile weapon True 2182 | mistress woman True 2183 | mob crowd True 2184 | modifier word True 2185 | mollusc animal True 2186 | mom parent True 2187 | monarch ruler True 2188 | monastery building True 2189 | monastery dwelling True 2190 | monastery house True 2191 | monastery housing True 2192 | monoclonal molecule True 2193 | monoclonal protein True 2194 | monsoon wind True 2195 | moratorium pause True 2196 | mortar weaponry True 2197 | mosque building True 2198 | motel building True 2199 | moth insect True 2200 | mother ancestor True 2201 | mother progenitor True 2202 | mother relative True 2203 | motorbike vehicle True 2204 | motorcycle vehicle True 2205 | motorist driver True 2206 | motorway highway True 2207 | motorway road True 2208 | motto saying True 2209 | mucosa tissue True 2210 | mule animal True 2211 | mule mammal True 2212 | multiculturalism doctrine True 2213 | mummy ancestor True 2214 | murderer criminal True 2215 | muse deity True 2216 | musket gun True 2217 | nanny adult True 2218 | nanotechnology discipline True 2219 | navy organization True 2220 | negation statement True 2221 | nematode invertebrate True 2222 | nerve tissue True 2223 | netball game True 2224 | neurology science True 2225 | neuroscience discipline True 2226 | neuroscience science True 2227 | nickname name True 2228 | nipple organ True 2229 | nostalgia feeling True 2230 | notary official True 2231 | noun word True 2232 | nurse adult True 2233 | nursing work True 2234 | oat cereal True 2235 | objectivity trait True 2236 | observatory building True 2237 | odour sensation True 2238 | odyssey travel True 2239 | officer serviceman True 2240 | oil lipid True 2241 | ointment drug True 2242 | olive fruit True 2243 | oncology discipline True 2244 | oncology science True 2245 | opium narcotic True 2246 | optimism feeling True 2247 | orange solid True 2248 | orator speaker True 2249 | orchid flower True 2250 | ore mineral True 2251 | organist performer True 2252 | osteoarthritis arthritis True 2253 | osteoarthritis illness True 2254 | outpost post True 2255 | overhead cost True 2256 | overpayment payment True 2257 | owl bird True 2258 | owl vertebrate True 2259 | ox animal True 2260 | oyster animal True 2261 | package collection True 2262 | paddle stick True 2263 | pair set True 2264 | palace dwelling True 2265 | pancreas organ True 2266 | panda animal True 2267 | panda mammal True 2268 | panda vertebrate True 2269 | panic fear True 2270 | parachute equipment True 2271 | parameter concept True 2272 | parapet wall True 2273 | parent relative True 2274 | parenthesis symbol True 2275 | parody caricature True 2276 | parrot vertebrate True 2277 | parser software True 2278 | passion feeling True 2279 | pathologist doctor True 2280 | pathology science True 2281 | patience trait True 2282 | pc computer True 2283 | pc machine True 2284 | pear fruit True 2285 | pear produce True 2286 | pearl jewel True 2287 | pearl jewelry True 2288 | penguin animal True 2289 | penguin bird True 2290 | penguin seabird True 2291 | penicillin antibiotic True 2292 | penis organ True 2293 | pennant signal True 2294 | pennant symbol True 2295 | penthouse housing True 2296 | peptide chemical True 2297 | percussionist performer True 2298 | perseverance trait True 2299 | pet animal True 2300 | petal leaf True 2301 | petroleum chemical True 2302 | petroleum oil True 2303 | pew bench True 2304 | pharmacology science True 2305 | pharmacy discipline True 2306 | pheasant animal True 2307 | pheasant vertebrate True 2308 | phonology science True 2309 | physician adult True 2310 | physician professional True 2311 | physiology biology True 2312 | physiology science True 2313 | physiotherapist therapist True 2314 | physiotherapy therapy True 2315 | physiotherapy treatment True 2316 | pianist entertainer True 2317 | pickup vehicle True 2318 | pig swine True 2319 | pigeon vertebrate True 2320 | pilgrimage journey True 2321 | pilot worker True 2322 | pine tree True 2323 | pipe conduit True 2324 | piper entertainer True 2325 | piper musician True 2326 | piper performer True 2327 | piracy crime True 2328 | pirate criminal True 2329 | pizza food True 2330 | platform surface True 2331 | platter ware True 2332 | playing show True 2333 | playlist information True 2334 | playlist list True 2335 | plum tree True 2336 | pocket container True 2337 | poet writer True 2338 | polarization phenomenon True 2339 | pollen spore True 2340 | polyethylene resin True 2341 | polymer chemical True 2342 | polymerase chemical True 2343 | polymerase enzyme True 2344 | pontoon boat True 2345 | pony horse True 2346 | pony mammal True 2347 | pope leader True 2348 | porter employee True 2349 | porter worker True 2350 | porter workman True 2351 | postcard mail True 2352 | postgraduate student True 2353 | postman worker True 2354 | potato food True 2355 | potato vegetable True 2356 | pouch container True 2357 | pram vehicle True 2358 | preamble section True 2359 | preconception belief True 2360 | prefecture district True 2361 | prelate clergyman True 2362 | premier representative True 2363 | preposition word True 2364 | president leader True 2365 | primacy standing True 2366 | primate priest True 2367 | princess aristocrat True 2368 | principle idea True 2369 | priory house True 2370 | privateer mariner True 2371 | privateer sailor True 2372 | probate document True 2373 | professorship occupation True 2374 | progenitor ancestor True 2375 | pronoun word True 2376 | propaganda information True 2377 | prosecutor official True 2378 | protein molecule True 2379 | pseudonym name True 2380 | psoriasis disease True 2381 | psoriasis illness True 2382 | psychiatry science True 2383 | psychoanalysis therapy True 2384 | psychoanalysis treatment True 2385 | psychoanalysis work True 2386 | psychology science True 2387 | psychotherapy discipline True 2388 | psychotherapy science True 2389 | publisher firm True 2390 | pudding food True 2391 | puppy mammal True 2392 | puppy vertebrate True 2393 | python animal True 2394 | python reptile True 2395 | python vertebrate True 2396 | quarterback player True 2397 | quartz solid True 2398 | questionnaire document True 2399 | rabbit vertebrate True 2400 | race contest True 2401 | racehorse mammal True 2402 | racing sport True 2403 | radar instrument True 2404 | radiation phenomenon True 2405 | radiotherapy care True 2406 | radiotherapy treatment True 2407 | radius magnitude True 2408 | rage emotion True 2409 | rain phenomenon True 2410 | rainforest vegetation True 2411 | rainwater water True 2412 | raisin produce True 2413 | range magnitude True 2414 | rat mammal True 2415 | raven vertebrate True 2416 | receiver equipment True 2417 | receptionist worker True 2418 | recovery improvement True 2419 | rectangle polygon True 2420 | rector leader True 2421 | red color True 2422 | reel equipment True 2423 | reelection election True 2424 | refreshment food True 2425 | regent member True 2426 | reggae music True 2427 | registry record True 2428 | reimbursement compensation True 2429 | reimbursement payment True 2430 | reindeer animal True 2431 | reliability trait True 2432 | relief feeling True 2433 | remorse feeling True 2434 | reptile animal True 2435 | reptile vertebrate True 2436 | resentment emotion True 2437 | reservist serviceman True 2438 | resident inhabitant True 2439 | resignation feeling True 2440 | retina tissue True 2441 | review appraisal True 2442 | revolver pistol True 2443 | rhino vertebrate True 2444 | rider traveler True 2445 | rifle weapon True 2446 | rig equipment True 2447 | roadway road True 2448 | roast meat True 2449 | robbery crime True 2450 | robin animal True 2451 | robin vertebrate True 2452 | rodent animal True 2453 | rodent mammal True 2454 | rodent vertebrate True 2455 | roofing equipment True 2456 | roster list True 2457 | royalty payment True 2458 | rucksack bag True 2459 | rue herb True 2460 | rugby game True 2461 | rum drug True 2462 | rum fluid True 2463 | rum liquid True 2464 | rune signal True 2465 | sack bag True 2466 | sadness feeling True 2467 | safari travel True 2468 | salesman employee True 2469 | salesman worker True 2470 | salmon animal True 2471 | salmon fish True 2472 | sandwich food True 2473 | sauna room True 2474 | sausage solid True 2475 | sawmill machine True 2476 | saxophonist performer True 2477 | scapegoat victim True 2478 | scarf garment True 2479 | schoolmaster educator True 2480 | scissors tool True 2481 | scourge instrument True 2482 | screen surface True 2483 | screenwriter writer True 2484 | screwdriver tool True 2485 | seabird bird True 2486 | seabird vertebrate True 2487 | seaman sailor True 2488 | seaplane airplane True 2489 | seaplane vehicle True 2490 | seawater water True 2491 | seaweed alga True 2492 | secret information True 2493 | secretariat organization True 2494 | sedan car True 2495 | sedan vehicle True 2496 | seminar gathering True 2497 | seminary institution True 2498 | serpent animal True 2499 | serpent reptile True 2500 | serpent vertebrate True 2501 | sewer conduit True 2502 | shareholder investor True 2503 | shark fish True 2504 | shaving cleaning True 2505 | shellfish seafood True 2506 | shellfish solid True 2507 | sherry beverage True 2508 | sherry liquid True 2509 | sherry wine True 2510 | shirt clothing True 2511 | shopkeeper merchant True 2512 | shortcut road True 2513 | shovel tool True 2514 | shower fixture True 2515 | shrine building True 2516 | silo tower True 2517 | sir man True 2518 | sis relative True 2519 | sixty integer True 2520 | size magnitude True 2521 | skating sport True 2522 | skier athlete True 2523 | skin covering True 2524 | skin tissue True 2525 | skull tissue True 2526 | slalom contest True 2527 | slogan saying True 2528 | sloop vehicle True 2529 | smallpox illness True 2530 | smuggler criminal True 2531 | snail animal True 2532 | snake animal True 2533 | snippet piece True 2534 | snooker game True 2535 | soccer game True 2536 | sociologist scientist True 2537 | sociology science True 2538 | soldier serviceman True 2539 | soloist musician True 2540 | soloist performer True 2541 | son offspring True 2542 | son relative True 2543 | song music True 2544 | soprano entertainer True 2545 | soprano performer True 2546 | soprano singer True 2547 | spacecraft equipment True 2548 | spaceship vehicle True 2549 | spaghetti food True 2550 | spaghetti pasta True 2551 | spasm symptom True 2552 | spear instrument True 2553 | spear weapon True 2554 | spectrometer instrument True 2555 | spinach herb True 2556 | spiral curve True 2557 | spokesman spokesperson True 2558 | spokeswoman advocate True 2559 | spokeswoman spokesperson True 2560 | spoon container True 2561 | spouse relative True 2562 | sprinter athlete True 2563 | squid solid True 2564 | stag animal True 2565 | stag mammal True 2566 | stagecoach vehicle True 2567 | stallion animal True 2568 | stallion horse True 2569 | staple commodity True 2570 | statesman leader True 2571 | stepfather ancestor True 2572 | stepmother ancestor True 2573 | stereo equipment True 2574 | stipend payment True 2575 | stocking commodity True 2576 | storyteller communicator True 2577 | strawberry berry True 2578 | strut walk True 2579 | studio workplace True 2580 | subcommittee organization True 2581 | subcontractor contractor True 2582 | submarine ship True 2583 | subtraction calculation True 2584 | suburb district True 2585 | suit commodity True 2586 | suitcase container True 2587 | sulphate chemical True 2588 | sundial instrument True 2589 | sunlight light True 2590 | sunshine phenomenon True 2591 | supercomputer computer True 2592 | supercomputer machine True 2593 | supper meal True 2594 | surcharge cost True 2595 | surgeon professional True 2596 | surprise feeling True 2597 | swan bird True 2598 | swap transaction True 2599 | sweater commodity True 2600 | sweetness sensation True 2601 | swimmer athlete True 2602 | swimming sport True 2603 | symphony music True 2604 | symphony sonata True 2605 | symposium meeting True 2606 | syringe instrument True 2607 | tank vehicle True 2608 | tanker ship True 2609 | tanker vehicle True 2610 | tar chemical True 2611 | taste sensation True 2612 | tavern building True 2613 | taxonomy hierarchy True 2614 | tea beverage True 2615 | teacher professional True 2616 | teaching occupation True 2617 | technician worker True 2618 | telegraph apparatus True 2619 | telephony telecommunication True 2620 | telescope instrument True 2621 | telly receiver True 2622 | temperament trait True 2623 | ten integer True 2624 | tenant payer True 2625 | tench animal True 2626 | tench fish True 2627 | term word True 2628 | terminal facility True 2629 | tern vertebrate True 2630 | terrier carnivore True 2631 | terrier dog True 2632 | terror emotion True 2633 | terror feeling True 2634 | textbook book True 2635 | theater building True 2636 | theatre building True 2637 | theft felony True 2638 | theology discipline True 2639 | therapy care True 2640 | thermostat regulator True 2641 | thesaurus publication True 2642 | thief criminal True 2643 | thirty integer True 2644 | thoroughfare road True 2645 | thrill emotion True 2646 | throne chair True 2647 | throne furniture True 2648 | thunderstorm storm True 2649 | ticket document True 2650 | tie clothing True 2651 | tip end True 2652 | title text True 2653 | toad animal True 2654 | toast bread True 2655 | toast food True 2656 | toddler child True 2657 | toe extremity True 2658 | tomorrow day True 2659 | tongue organ True 2660 | tortoise animal True 2661 | tortoise reptile True 2662 | tour travel True 2663 | traction phenomenon True 2664 | traitor criminal True 2665 | transplantation procedure True 2666 | trolley vehicle True 2667 | trouser garment True 2668 | trumpeter entertainer True 2669 | trumpeter performer True 2670 | tsunami wave True 2671 | tuberculosis disease True 2672 | tummy tissue True 2673 | tumor illness True 2674 | tumour illness True 2675 | turbine engine True 2676 | turkey animal True 2677 | turkey bird True 2678 | turnpike gate True 2679 | turquoise crystal True 2680 | turret tower True 2681 | tutor teacher True 2682 | twelve integer True 2683 | twenty integer True 2684 | tycoon businessman True 2685 | typhoon phenomenon True 2686 | typhoon storm True 2687 | typography occupation True 2688 | tyrant ruler True 2689 | ultimatum request True 2690 | underside boundary True 2691 | underwear clothing True 2692 | uprising conflict True 2693 | uterus organ True 2694 | value idea True 2695 | vandalism mischief True 2696 | vegan eater True 2697 | veil garment True 2698 | velocity rate True 2699 | velvet fabric True 2700 | vertebrate animal True 2701 | vertex point True 2702 | vi digit True 2703 | vial container True 2704 | vicar clergyman True 2705 | vicar leader True 2706 | vicar priest True 2707 | vicarage building True 2708 | vicarage dwelling True 2709 | vicinity area True 2710 | victimisation practice True 2711 | vintage beverage True 2712 | vintage liquid True 2713 | violinist entertainer True 2714 | virus microorganism True 2715 | visualisation representation True 2716 | vocalist performer True 2717 | vodka alcohol True 2718 | voice sound True 2719 | vole animal True 2720 | vole rodent True 2721 | vole vertebrate True 2722 | volleyball game True 2723 | volleyball sport True 2724 | vulture vertebrate True 2725 | wader bird True 2726 | wader vertebrate True 2727 | wage payment True 2728 | waiter employee True 2729 | waitress employee True 2730 | waitress waiter True 2731 | waitress worker True 2732 | walnut nut True 2733 | walnut seed True 2734 | warbler entertainer True 2735 | warbler performer True 2736 | warbler singer True 2737 | warrant document True 2738 | warship vehicle True 2739 | washer worker True 2740 | waterfowl animal True 2741 | weakening transformation True 2742 | weapon instrument True 2743 | webcam camera True 2744 | wheat cereal True 2745 | whiskey drug True 2746 | whiskey fluid True 2747 | whiskey liquid True 2748 | whiskey liquor True 2749 | whisky beverage True 2750 | whisky fluid True 2751 | wife spouse True 2752 | windfall fruit True 2753 | wine alcohol True 2754 | wine fluid True 2755 | winger athlete True 2756 | winner contestant True 2757 | wolf carnivore True 2758 | wolf vertebrate True 2759 | woman adult True 2760 | woodpecker animal True 2761 | woodpecker bird True 2762 | workbook publication True 2763 | worm invertebrate True 2764 | wrath emotion True 2765 | writer communicator True 2766 | yearning feeling True 2767 | yellow color True 2768 | yesterday day True 2769 | yoghurt food True 2770 | zeal feeling True 2771 | zebra animal True 2772 | -------------------------------------------------------------------------------- /data/binary/turney2014.tsv: -------------------------------------------------------------------------------- 1 | word1 word2 label 2 | abbey nun True 3 | abode house True 4 | absolve sinner True 5 | abundance destitution False 6 | abundant scarce False 7 | abuse discipline True 8 | acceleration speed True 9 | accept reject False 10 | accident damage True 11 | account history True 12 | acknowledgement wave False 13 | acne adolescence False 14 | active tired False 15 | actor audition False 16 | addict use False 17 | administrator power True 18 | adolescence acne False 19 | adolescence puberty False 20 | adorable cute True 21 | adore love False 22 | adulthood independence False 23 | adulthood job False 24 | adulthood responsibility False 25 | advertisement desire True 26 | airplane cockpit True 27 | airplane fly False 28 | airport terminal True 29 | aisle supermarket False 30 | album photo True 31 | album song True 32 | alcohol drunkenness True 33 | alcohol party False 34 | alcoholic drinking True 35 | alive destroy False 36 | allergy breathing True 37 | amputation body True 38 | amusement laughter False 39 | analysis intelligent True 40 | anaphylaxis antihistamine False 41 | anatomy body True 42 | anatomy body True 43 | ancient modern False 44 | anger snarl False 45 | anger yell False 46 | angry belligerence True 47 | angry confront False 48 | angry enraged False 49 | angry frowning False 50 | angry furious True 51 | angry scream False 52 | animal pig False 53 | animal vet False 54 | animal zoo False 55 | animal dog False 56 | anorexic thin True 57 | answer question False 58 | ant insect True 59 | anthropology human True 60 | anthropology people True 61 | antihistamine anaphylaxis False 62 | antiquity walker False 63 | aphrodisiac lust True 64 | apologize offended False 65 | apple company True 66 | apple food True 67 | apple fruit True 68 | apple orchard False 69 | apple fruit True 70 | aquarium fish True 71 | architect drawing False 72 | architecture building True 73 | architecture model True 74 | argue contentious False 75 | argue debate True 76 | armistice peace True 77 | army soldier True 78 | army soldier True 79 | arrhythmia heartbeat True 80 | arrive drive False 81 | arrogance confident True 82 | arsenal weapon True 83 | art artist False 84 | art sculpture False 85 | arthur king True 86 | artist art False 87 | artist masterpiece False 88 | artist paint False 89 | artistic creative False 90 | artistic paint False 91 | artwork replica False 92 | ascetic austerity True 93 | ash tree True 94 | ask answer True 95 | asking negotiating False 96 | aspirin healing True 97 | associate partner False 98 | atheist christian False 99 | atheist worship False 100 | athlete body False 101 | athlete competition False 102 | athlete fit True 103 | athlete medal False 104 | atlantic ocean True 105 | atmosphere gas True 106 | attack fight True 107 | attack strategy True 108 | attraction stalking False 109 | audible listen False 110 | audience perform False 111 | audition actor True 112 | automobile transportation True 113 | automobile trunk True 114 | avidity eagerness False 115 | azalea bush True 116 | baby midwife False 117 | baby bald True 118 | baby helpless True 119 | baby nurse False 120 | baby parent False 121 | back chair False 122 | backpack youth False 123 | badge authority True 124 | bake toast False 125 | baker bread True 126 | bakery cake True 127 | baking mixing True 128 | ballerina grace True 129 | ballpoint pen True 130 | banana nourishment True 131 | band musician True 132 | bandage sling False 133 | bank loan True 134 | bank money True 135 | bank river True 136 | bank stream True 137 | baptism priest True 138 | bar cocktail True 139 | barbeque fire False 140 | barber scissors False 141 | bark cat False 142 | barnyard henhouse True 143 | baseball pitch True 144 | baseball pitching True 145 | baseboard wall True 146 | basil herb True 147 | basketball dribbling True 148 | basketball shooting True 149 | bath cleanliness True 150 | bathe dirtiness False 151 | bathing shampooing True 152 | bathroom lavatory True 153 | bathroom restroom True 154 | bathtub water False 155 | baton conductor False 156 | battered fix False 157 | battery controller False 158 | battery phone False 159 | beach dune True 160 | beach sand True 161 | beat defeated True 162 | beautiful plain False 163 | beautiful pretty True 164 | beauty scar False 165 | bed hospital False 166 | bedroom bed True 167 | beef meat True 168 | beg request True 169 | believe faith False 170 | bell dinner True 171 | bellicose irenic False 172 | below above False 173 | bent inflexible False 174 | best inferior False 175 | beverage water False 176 | beverage soda False 177 | beverage tea False 178 | bicycle wheel True 179 | big large True 180 | bigot hateful True 181 | biology life True 182 | biology organism True 183 | bird cardinal False 184 | bird feather True 185 | bird lip False 186 | bird swan False 187 | bird wing True 188 | black white False 189 | blackmail negotiate True 190 | blanket soft True 191 | blemish skin True 192 | blender puree False 193 | blindness vision True 194 | blood droplet True 195 | blood tree False 196 | blouse clothes True 197 | blow pain True 198 | blue color True 199 | boat motor True 200 | boat ship True 201 | body anatomy False 202 | body clothes False 203 | body flesh True 204 | bolt nut False 205 | bone brittle True 206 | bone fracture False 207 | book chapter True 208 | book chapter True 209 | book literature True 210 | book page True 211 | book page True 212 | book spine True 213 | book story True 214 | book summary False 215 | bookcase shelf True 216 | book library False 217 | book scholar False 218 | boost price True 219 | boot footwear True 220 | boot shoe True 221 | boot leather True 222 | boredom activity False 223 | borrow take False 224 | borrower lender False 225 | botany plant True 226 | bouquet flower True 227 | bowl dish True 228 | bowl glass False 229 | box cardboard True 230 | boxer fight False 231 | box warehouse False 232 | boyhood man False 233 | bread baker False 234 | bread dough False 235 | bread flour True 236 | break crack True 237 | break fragile False 238 | break frangible False 239 | break repair False 240 | break sturdy False 241 | breathe dead False 242 | breeze spring False 243 | brick wall False 244 | bright dull False 245 | brightness star False 246 | brittle bone False 247 | broken fix False 248 | broken useable False 249 | broken whole False 250 | broom maid False 251 | brush hair False 252 | brush teeth False 253 | building floor True 254 | building hammering True 255 | building lobby True 256 | building wall True 257 | bulb light True 258 | bullet gun False 259 | bumper ding False 260 | bumping volleyball False 261 | bunch grape True 262 | burka body True 263 | burn hot False 264 | burned wooden False 265 | burning hot True 266 | burnt overcooked True 267 | bus passenger True 268 | bus transportation True 269 | bush azalea False 270 | bush root True 271 | bush trap True 272 | buyer salesperson False 273 | buyer seller False 274 | buzzer end True 275 | cacophony howl True 276 | cake slice True 277 | calculator add False 278 | calculator keyboard False 279 | call phone False 280 | calm windy False 281 | camaro car True 282 | camera film False 283 | candy halloween False 284 | candy sweet True 285 | candy sweet True 286 | car bus False 287 | car camaro False 288 | car factory False 289 | car garage False 290 | car key False 291 | car wheel True 292 | cardinal bird True 293 | careful cautious True 294 | careful reckless False 295 | caring overbearing False 296 | carnival ride True 297 | carpet fiber True 298 | carpet vacuum False 299 | carrot vegetable True 300 | car ford False 301 | car racetrack False 302 | case evidence True 303 | cashew nut True 304 | castigate criticize True 305 | castle moat True 306 | cat pet True 307 | cat whisker True 308 | catastrophic beneficial False 309 | catcher fastball False 310 | cat animal True 311 | caution flashing False 312 | cautious careful True 313 | cave entrance True 314 | cd scratch False 315 | ceiling sky False 316 | ceiling wall True 317 | celebrant party False 318 | celebration birthday False 319 | celebration firework False 320 | cell body True 321 | cello violin False 322 | cellphone mobile True 323 | cement solid True 324 | certain perplexed False 325 | chain link True 326 | chair back True 327 | chair cushion False 328 | chair furniture True 329 | chair leg True 330 | chair leg True 331 | chair seat True 332 | chair furniture True 333 | chalk blackboard False 334 | chalkboard teacher False 335 | champion trophy False 336 | changed permanent False 337 | chant prayer False 338 | chapter page True 339 | charity donation False 340 | charles prince True 341 | chef knife False 342 | chef restaurant False 343 | chemistry element True 344 | cherry red True 345 | chewing eating False 346 | chihuahua dog True 347 | child innocence True 348 | child kid True 349 | child nanny False 350 | child youth True 351 | chip porcelain True 352 | chip snack True 353 | chisel tool True 354 | choice option True 355 | choreography performance False 356 | church nave True 357 | church preacher True 358 | church sanctuary True 359 | circus clown True 360 | circus ringmaster True 361 | citation violation True 362 | city block True 363 | city map True 364 | city urban True 365 | clambake clam True 366 | clam clambake False 367 | clarify muddled False 368 | clarinet instrument True 369 | class student True 370 | classroom student True 371 | clay malleable True 372 | clean bathe False 373 | clean dirty False 374 | clean messy False 375 | clean tidy True 376 | clean wash False 377 | cleaning dusting True 378 | cleanliness bath False 379 | clearing forest True 380 | client attorney False 381 | client lawyer False 382 | cliff edge True 383 | clock hand True 384 | closet clothes True 385 | closet clothing True 386 | cloth fiber True 387 | cloth stitch False 388 | clothes blouse False 389 | clothes body True 390 | clothes closet False 391 | clothes dresser False 392 | clothes iron False 393 | clothing dress False 394 | clothing figure True 395 | clothing mend False 396 | clothing thread True 397 | cloud moisture True 398 | cluttered organize False 399 | coal mine False 400 | coat warmth True 401 | cobra snake True 402 | cocktail alcohol True 403 | cocktail bar False 404 | code message True 405 | code programmer False 406 | coerce persuade True 407 | coffin death False 408 | coffin funeral False 409 | cold heat False 410 | cold hot False 411 | cold sneeze True 412 | cold snow False 413 | cold warm False 414 | cold winter False 415 | collar dog False 416 | collect fee False 417 | college degree False 418 | college teacher True 419 | collie dog True 420 | color red False 421 | combustion fire True 422 | comedy movie True 423 | commercial viewer True 424 | companionship dog False 425 | company employee True 426 | compass direction True 427 | compassionate heartless False 428 | competition athlete True 429 | complain whine False 430 | composer song False 431 | composition outline True 432 | compost fertilizer False 433 | computer chip True 434 | computer monitor False 435 | computer office False 436 | computer programmer False 437 | computer screen True 438 | concert musician True 439 | concrete cement True 440 | confront angry False 441 | confused wandering False 442 | confusion illogical False 443 | consume edible False 444 | contentment happy True 445 | controller battery False 446 | convict behave False 447 | cook meal False 448 | cooking chopping True 449 | cooking frying True 450 | cooking peeling True 451 | cooking slicing True 452 | cooking stirring True 453 | cordiality handshake False 454 | corpse death True 455 | costume gender True 456 | couch arm True 457 | couch furniture True 458 | couch sofa True 459 | cough illness True 460 | cough sickness True 461 | coupe sedan False 462 | courageous coward False 463 | coward fear True 464 | cower hero False 465 | cow animal True 466 | crack glass True 467 | crack mirror True 468 | crack sidewalk True 469 | craggy smooth False 470 | cramp aching True 471 | crash noise True 472 | creative artistic False 473 | crime evidence True 474 | criminal execute False 475 | criminal handcuff False 476 | criminal sentence False 477 | criminology crime True 478 | criticize castigate False 479 | criticize praise False 480 | cross christianity True 481 | cross faith True 482 | crossbones poison True 483 | crown king True 484 | crown royalty True 485 | crown sovereignty True 486 | crow bird True 487 | cruel help False 488 | cruel kindness False 489 | cruelty kind False 490 | crust pie True 491 | cry happy False 492 | cry help True 493 | cry mourning True 494 | cry sad True 495 | cry sadness False 496 | cry emotional True 497 | cry sad True 498 | cry sadness True 499 | cry sobbing False 500 | cup rim True 501 | cupboard dish True 502 | cure disease False 503 | cured sick False 504 | curious investigation True 505 | currency dollar False 506 | curtain window True 507 | curtain room True 508 | cushion pillow False 509 | customer sell False 510 | cute adorable True 511 | cutlery fork False 512 | cylinder bottle False 513 | dahlia flower True 514 | dairy milk True 515 | daisy flower True 516 | dallas city True 517 | damage accident False 518 | dance step True 519 | dandruff shampoo False 520 | dark bright False 521 | dark light False 522 | darken color True 523 | darkness light False 524 | darkness sun False 525 | data encryption False 526 | dead rot False 527 | deaf hearing False 528 | deafness hearing True 529 | deal contract True 530 | death corpse False 531 | death population True 532 | debtor payment False 533 | deception honesty False 534 | deck ship False 535 | decline health True 536 | decoy motif True 537 | decrescendo sound True 538 | deed owner False 539 | deepen flavor True 540 | deer fawn False 541 | defiant punish False 542 | defiantly cooperate False 543 | degree college False 544 | delicately fight False 545 | delicious disgusting False 546 | dense sink False 547 | deposit balance True 548 | depressed dismayed True 549 | depression mind True 550 | depression sad True 551 | depression sadness True 552 | dermatology skin True 553 | desert evergreen False 554 | desert flood False 555 | desire advertisement False 556 | desk furniture True 557 | desk table False 558 | desk wood True 559 | despair joy False 560 | despair sadness False 561 | destroy alive False 562 | destroyed reparable False 563 | destruction war False 564 | determined certainty True 565 | development draft False 566 | development plan True 567 | diamond shiny True 568 | diana princess True 569 | difficult easy False 570 | dig ditch False 571 | dig hole True 572 | dim bright False 573 | dim light True 574 | dime money True 575 | ding bumper True 576 | dinner bell False 577 | dinner meal True 578 | diploma education True 579 | diploma graduate False 580 | diploma graduation False 581 | direction route False 582 | dirt cleanliness False 583 | dirtied clean False 584 | dirty bathe False 585 | dirty clean False 586 | disarray messy False 587 | disarrayed neaten False 588 | discard litter False 589 | discipline abuse False 590 | discontent frown False 591 | discreet loud False 592 | discrimination separate True 593 | disdain hatred False 594 | disease cure False 595 | disease health False 596 | disease medicine False 597 | disease sickness True 598 | disgusting delicious False 599 | disgusting tasty False 600 | dish bowl False 601 | dish soap False 602 | dishonesty lie False 603 | disloyal friend False 604 | dismantle destroyed True 605 | ditch road True 606 | divide part True 607 | doctor degree True 608 | doctor hurt False 609 | documentary event True 610 | dog animal True 611 | dog collar False 612 | dog companionship True 613 | dog furry True 614 | dog leash False 615 | dog pet True 616 | dog tail True 617 | dog animal True 618 | dog pet True 619 | dollar coin True 620 | dollar currency True 621 | donate miserly False 622 | donate selfish False 623 | done doable False 624 | door inside True 625 | dorm student False 626 | down up False 627 | doze sleep True 628 | draft development True 629 | draft essay False 630 | drain tub False 631 | drank drink False 632 | drawing picture False 633 | drawing sketch True 634 | dream fantasize True 635 | dress pattern True 636 | dress seamstress False 637 | dresser clothes True 638 | dress clothing True 639 | drink drank False 640 | drink milk False 641 | drink slurp False 642 | drink wine False 643 | drinking alcoholic False 644 | droplet blood False 645 | drown swim False 646 | drug pharmacology False 647 | drunk intoxication True 648 | drunkenness alcohol False 649 | dry wet False 650 | dryness moisturize False 651 | dryness ocean False 652 | dryness rain False 653 | dull bright False 654 | dumb witty False 655 | dune beach True 656 | dust housekeeper False 657 | dwelling house True 658 | dynamite explode False 659 | ear lobe True 660 | earring ear False 661 | earth planet True 662 | earthworm segment True 663 | easy difficult False 664 | eat cook False 665 | eat cooked False 666 | eat delicious False 667 | eat edible False 668 | eat satisfaction True 669 | eating chewing True 670 | eating fullness True 671 | economics market True 672 | ecstatic angry False 673 | ecstatic disgruntled False 674 | ecstatic joyful True 675 | edge cliff True 676 | education diploma False 677 | education enlightenment True 678 | education expertise True 679 | education student False 680 | egg yolk True 681 | egg omelette False 682 | egotism selfish True 683 | egypt country True 684 | elaborateness frugality False 685 | elephant herd False 686 | elevate raise True 687 | embarrassed blush False 688 | embrace abandon False 689 | emotional turmoil True 690 | employee check False 691 | employee contract False 692 | employee job True 693 | employee manager False 694 | emptiness fill False 695 | empty fill False 696 | empty full False 697 | encryption data True 698 | enemy fight False 699 | engagement wedding True 700 | ennui boredom False 701 | enraged angry True 702 | entertained bored False 703 | enthusiasm apathetic False 704 | enthusiastic lazy False 705 | entomology insect True 706 | entrepreneur wealth True 707 | envelop surrounded True 708 | equation formula True 709 | equator hemisphere True 710 | equator hemisphere True 711 | erie lake True 712 | eruption angry True 713 | essay draft True 714 | evanescent gone False 715 | evening day False 716 | event documentary False 717 | event photograph False 718 | event journal True 719 | evergreen desert False 720 | evidence case False 721 | evidence crime False 722 | evil angelic False 723 | evil good False 724 | excellent mediocre False 725 | excitement happy True 726 | execute criminal False 727 | exempted excused False 728 | exercise fatigue True 729 | exercise fitness True 730 | exercising stretching True 731 | exhausted run False 732 | exhausted tired True 733 | exhaustion sigh False 734 | experience confidence True 735 | experience novice False 736 | expert experience True 737 | expert knowledge True 738 | explode dynamite False 739 | explosion damage True 740 | express speak False 741 | eye sunglass False 742 | eyeshadow makeup True 743 | face makeup False 744 | face pimple False 745 | factory car True 746 | factory good True 747 | factory product True 748 | factory tire True 749 | fairy wand False 750 | fairytale ideal True 751 | faith believe False 752 | faith cross False 753 | fall slowly False 754 | family father False 755 | fantasize dream True 756 | farm tractor True 757 | farmer crop True 758 | fashion designer False 759 | fast glutton False 760 | fast run False 761 | fast slow False 762 | fat skinny False 763 | fat thin False 764 | father family True 765 | faucet pipe False 766 | foot inch True 767 | female male False 768 | fetus miscarriage False 769 | fidelity devotion True 770 | fight enemy True 771 | fight pacifist False 772 | fight war False 773 | fill empty False 774 | film movie False 775 | finger ring False 776 | fire burn False 777 | fire burn True 778 | fire burnt True 779 | fire heat True 780 | fire hot True 781 | fire warmth True 782 | fireplace wood False 783 | fish fin True 784 | fish trout False 785 | fishing lake False 786 | fix battered False 787 | fix repaired True 788 | fixed irreparable False 789 | fizzy pop False 790 | flag nation True 791 | flame blister True 792 | flashing caution True 793 | flashlight battery False 794 | flashlight bulb True 795 | flat plain False 796 | flesh body False 797 | flimsy paper False 798 | flirt seduce False 799 | flirtation tryst False 800 | float buoyant False 801 | flock bird True 802 | flock sheep True 803 | flood water True 804 | floor building False 805 | floor clean False 806 | floor wall True 807 | florist flower False 808 | flower stem True 809 | flute instrument True 810 | fly airplane False 811 | follower inspire False 812 | food apple False 813 | food cook False 814 | food fridge False 815 | food fullness True 816 | food meal False 817 | food nourishment True 818 | food satiation True 819 | food satiety True 820 | fooled cunning False 821 | foot inch True 822 | foot shoe False 823 | foot toe True 824 | football playbook True 825 | force persuade True 826 | force pressure True 827 | ford car True 828 | forest clearing True 829 | forest tree True 830 | forest tree True 831 | forgive sin False 832 | forgiving vengeful False 833 | fork cutlery True 834 | fork utensil True 835 | form mold True 836 | fornicate priest False 837 | forward backward False 838 | fracture bone True 839 | fragile damaged False 840 | frame photograph True 841 | frame picture True 842 | frame window True 843 | frantic worried True 844 | freedom hostage False 845 | freedom prisoner False 846 | freedom slavery False 847 | fridge appliance True 848 | fridge food True 849 | friendly hostile False 850 | frigid cold True 851 | frosting cake True 852 | frown discontent True 853 | frown distaste True 854 | frown sadness True 855 | frowning angry True 856 | frozen thaw False 857 | frugality thrifty True 858 | fruit grape False 859 | fun boring False 860 | fun reserved False 861 | funeral coffin True 862 | funeral corpse True 863 | funeral joy False 864 | funeral mourner True 865 | funny boring False 866 | furniture chair False 867 | gallon ounce True 868 | gallon quart True 869 | game instruction True 870 | game player True 871 | game referee True 872 | game rule True 873 | gap teeth True 874 | garage car True 875 | garden flower True 876 | garden flower True 877 | garden vegetable True 878 | gas atmosphere False 879 | gas furnace False 880 | gasoline fuel True 881 | gate lock False 882 | gender costume False 883 | geology earth True 884 | geology rock True 885 | germ sickness True 886 | giddy happiness True 887 | gift recipient False 888 | give receiver True 889 | glare anger True 890 | glare look True 891 | glass pane True 892 | glass shattered False 893 | glass silicone True 894 | glass spectacle True 895 | glue adhesion True 896 | glue sticky True 897 | go come False 898 | goad placid False 899 | goal score True 900 | golden gleam False 901 | golf drive True 902 | good wrong False 903 | goose duck False 904 | goose gosling False 905 | gorge eat True 906 | gorilla mammal True 907 | gossip chat True 908 | gossip talk True 909 | grace ballerina False 910 | grading testing True 911 | gradually surprise False 912 | graduation diploma True 913 | graduation student True 914 | grant scientist False 915 | grape fruit True 916 | graphic stencil True 917 | greed miser False 918 | green color True 919 | green go True 920 | grief loss False 921 | grieving mourning True 922 | grimace disgust True 923 | groan pain True 924 | grocery list True 925 | groom horse True 926 | groom unkempt False 927 | grope touch True 928 | grotesque homely True 929 | growth incubation False 930 | guardrail highway True 931 | guest party False 932 | gun bullet False 933 | gun shooter False 934 | gym muscle True 935 | hair brush False 936 | hair hat False 937 | hair wig True 938 | hall music True 939 | halloween autumn False 940 | halloween candy False 941 | halved whole False 942 | ham meat True 943 | hammer pound False 944 | hammer tool True 945 | hammer toolbox False 946 | hand finger True 947 | hand glove False 948 | handle mug False 949 | hand soap False 950 | handshake agreement True 951 | handshake cordiality True 952 | hangar airplane True 953 | hangnail fingertip True 954 | happiness giddy False 955 | happiness joy False 956 | happiness laugh False 957 | happiness smile False 958 | happy contentment True 959 | happy heartbroken False 960 | happy smiling True 961 | hard simple False 962 | harmed invulnerable False 963 | harvest reaping False 964 | harvesting farming True 965 | hat hair True 966 | hat sombrero False 967 | headstone marble True 968 | heal hurt False 969 | heal injure False 970 | heal injured False 971 | health decline False 972 | healthy exercise False 973 | hearing deaf False 974 | hearing understanding False 975 | heart beat False 976 | heartless compassionate False 977 | heat cold False 978 | heat hot True 979 | heat sweat False 980 | heat temperature True 981 | heat warm True 982 | heater warmth True 983 | heaven christian False 984 | heaven sinner False 985 | hedge fence False 986 | help cry False 987 | help helpless False 988 | hem skirt True 989 | hemisphere equator True 990 | hemisphere equator True 991 | hen rooster False 992 | henry king True 993 | herd antelope True 994 | herd cow True 995 | herd elephant True 996 | hero honor False 997 | hero medal False 998 | heroin euphoria True 999 | hideous beautiful False 1000 | hideous ugly True 1001 | highway guardrail True 1002 | highway road False 1003 | hill mountain False 1004 | hill ramp False 1005 | hill top True 1006 | history past True 1007 | hit aggressive True 1008 | hit injury True 1009 | hive bee True 1010 | hole pant True 1011 | holiness saint False 1012 | home foyer True 1013 | home house True 1014 | home kitchen True 1015 | homeowner home True 1016 | homework graduate False 1017 | honda car True 1018 | honest deceptive False 1019 | honest liar False 1020 | honesty deception False 1021 | honey sweetness True 1022 | honor hero True 1023 | hood hair True 1024 | hood head True 1025 | hop rabbit False 1026 | hose leg True 1027 | hospital patient True 1028 | hospital wing True 1029 | hot burning False 1030 | hot cold False 1031 | hot fire False 1032 | hotel lobby True 1033 | hour second True 1034 | house abode True 1035 | house bedroom True 1036 | house brick True 1037 | house dwelling True 1038 | house home True 1039 | house paint False 1040 | house porch True 1041 | house roof True 1042 | house room True 1043 | hug comfort True 1044 | humble arrogant False 1045 | hunger food False 1046 | hunger starving False 1047 | hungry satiated False 1048 | hurt cry False 1049 | hurt doctor False 1050 | hurt victim True 1051 | hurting comfort False 1052 | husband widow False 1053 | hydration water False 1054 | hyperventilate breathe True 1055 | hyperventilating breathing True 1056 | hypothermia chilled True 1057 | ice cold True 1058 | ice melt False 1059 | ice water True 1060 | idea invention False 1061 | idiot stupidity True 1062 | ignorance learning True 1063 | ignorance sage False 1064 | ignorant bliss True 1065 | ignorant intelligent False 1066 | ignorant teach False 1067 | illness discomfort True 1068 | illogical confusion True 1069 | illuminate bright False 1070 | image photograph False 1071 | impenetrable destroyed False 1072 | imprison convict True 1073 | imprisoned free False 1074 | in out False 1075 | inarticulate express False 1076 | incapability ability False 1077 | increment number True 1078 | independence adulthood False 1079 | indian ocean True 1080 | inert mobile False 1081 | inexperience novice False 1082 | infant understand False 1083 | infertility reproduction True 1084 | infinite end False 1085 | inflation price True 1086 | ingredient recipe False 1087 | injure heal False 1088 | injury hit False 1089 | injury pain True 1090 | innocence child False 1091 | inside door True 1092 | insist assert True 1093 | insomnia sleep True 1094 | inspire follower True 1095 | instruct subordinate True 1096 | instruct teach True 1097 | instrument musician False 1098 | instrument violin False 1099 | insult kindly False 1100 | insult unkind True 1101 | integrity dishonest False 1102 | intelligence stupid False 1103 | interesting tedious False 1104 | internet website False 1105 | intransigent resist False 1106 | introduction conclusion False 1107 | introduction speech False 1108 | invalid illness True 1109 | invalid sickness True 1110 | invention idea True 1111 | investigation curious False 1112 | investor investment True 1113 | invincibility weak False 1114 | invincible defeated False 1115 | invisible color False 1116 | invisible sight False 1117 | ireland country True 1118 | iron blacksmith False 1119 | iron clothes False 1120 | iron pressed True 1121 | irreparable fixed False 1122 | irritation rage False 1123 | jean zipper True 1124 | jeer laugh True 1125 | jewelry ring False 1126 | jewelry ring False 1127 | job retiree False 1128 | jobless employed False 1129 | jog exercise False 1130 | joke laughter True 1131 | journey map True 1132 | journey step False 1133 | joy depression False 1134 | joy despair False 1135 | joyful ecstatic True 1136 | jubilation melancholy False 1137 | jug container True 1138 | key lock False 1139 | key car False 1140 | kid child True 1141 | kill hurt True 1142 | kill shoot False 1143 | kind rude False 1144 | king arthur False 1145 | king henry False 1146 | kiss love True 1147 | kiss passion True 1148 | kiss passionate True 1149 | kissing loving True 1150 | kitchen food True 1151 | kitchen home False 1152 | kitchen pot False 1153 | kitchen potholder False 1154 | knife butcher False 1155 | knitting purling True 1156 | know read False 1157 | knowledge expert False 1158 | knowledge ignorance False 1159 | kowtow compliment True 1160 | lake fishing True 1161 | lake shore True 1162 | lamb sheep False 1163 | lamp sun False 1164 | language linguistics False 1165 | laptop computer True 1166 | large big True 1167 | laugh amusement True 1168 | laugh happiness True 1169 | laugh happy True 1170 | laugh hilarity True 1171 | laughing amusement True 1172 | laughter amusement True 1173 | laughter joke False 1174 | lavatory bathroom True 1175 | lawn grass True 1176 | lawyer client False 1177 | lawyer client True 1178 | lay sleep False 1179 | lazily hurry False 1180 | lazy indolence True 1181 | lazy productive False 1182 | lead member True 1183 | leaf animal False 1184 | learn read False 1185 | learn student False 1186 | learning ignorance False 1187 | learning study False 1188 | leased rent False 1189 | leather boot False 1190 | lecture child True 1191 | leg chair False 1192 | leg snake False 1193 | lesson plan True 1194 | lethargic fatigue True 1195 | letter word True 1196 | lettuce salad False 1197 | leukemia blood True 1198 | liar honest False 1199 | liar honesty False 1200 | library book True 1201 | library book True 1202 | library reading False 1203 | license permission True 1204 | lie dishonesty True 1205 | lie exaggerate True 1206 | lie honestly False 1207 | lie whereabouts True 1208 | lie untrustworthy True 1209 | life biography True 1210 | life corpse False 1211 | light bright True 1212 | light carried False 1213 | light dark False 1214 | liked detested False 1215 | linguistics language True 1216 | liquid solid False 1217 | list grocery False 1218 | listen audible False 1219 | lit flammable False 1220 | litter discard True 1221 | lobby building True 1222 | lobby hotel False 1223 | lock security True 1224 | lock theft False 1225 | loneliness socialize False 1226 | look glare False 1227 | loss grief True 1228 | lost wandering False 1229 | loud discreet False 1230 | loudly whisper False 1231 | love affection True 1232 | love eternal True 1233 | low raise False 1234 | lower raise False 1235 | lower volume True 1236 | lust aphrodisiac False 1237 | lust attraction True 1238 | lust passionate True 1239 | mad anger True 1240 | magnanimous peace True 1241 | mailbox flag True 1242 | make manufacture True 1243 | makeup blemish True 1244 | makeup blemish True 1245 | makeup face True 1246 | makeup wrinkle True 1247 | mall shop True 1248 | mammal gorilla False 1249 | mammal hair True 1250 | man woman False 1251 | manager employee False 1252 | mania enthusiasm True 1253 | mansion room True 1254 | manufacture make True 1255 | map topography False 1256 | marble headstone False 1257 | mare stallion False 1258 | margin page True 1259 | margin paper True 1260 | marina boat True 1261 | mask face True 1262 | masochist suffering False 1263 | masterpiece artist False 1264 | mathematics number True 1265 | mature baby False 1266 | mature childish False 1267 | meal cook False 1268 | meal food True 1269 | mechanic tool False 1270 | medal athlete False 1271 | medal hero False 1272 | mediate relaxing True 1273 | mediator reconciliation False 1274 | medicate sickness False 1275 | medication prescription True 1276 | medicine disease False 1277 | medicine pharmacy False 1278 | medicine recovery True 1279 | mediocre excellent False 1280 | meet athlete True 1281 | meeting agenda True 1282 | melancholy jubilation False 1283 | melt density True 1284 | melt ice False 1285 | memphis city True 1286 | messy clean False 1287 | messy disarray True 1288 | messy sloppy False 1289 | messy tidy False 1290 | meteorology atmosphere True 1291 | meteorology weather True 1292 | mica mineral True 1293 | michigan lake True 1294 | microphone singer False 1295 | middle beginning False 1296 | milk dairy False 1297 | milk drink True 1298 | mill flour True 1299 | millionaire rich True 1300 | millionaire wealth True 1301 | mine coal True 1302 | mine coal True 1303 | mirror crack False 1304 | miscarriage pregnancy True 1305 | miser greed True 1306 | miser saving True 1307 | miser splurge False 1308 | miser squander False 1309 | mix blend True 1310 | moat castle True 1311 | mobile cellphone True 1312 | mobile inert False 1313 | model instruction True 1314 | modern ancient False 1315 | mogul wealth True 1316 | moisturize lotion False 1317 | money millionaire False 1318 | money paper True 1319 | money poor False 1320 | monitor computer False 1321 | monochromatic rainbow False 1322 | monotonous tedious True 1323 | morning sunrise False 1324 | morose sadness True 1325 | mother child True 1326 | motor boat False 1327 | mountain move False 1328 | mountain valley True 1329 | mourner funeral False 1330 | mourning cry False 1331 | mouse computer False 1332 | mouse rodent True 1333 | move mountain False 1334 | movie comedy False 1335 | movie preview False 1336 | movie scene True 1337 | movie screenplay True 1338 | movie script True 1339 | murderer evil True 1340 | murderer help False 1341 | muscle gym False 1342 | musical sing False 1343 | musician applause False 1344 | musician instrument False 1345 | musician music True 1346 | mustang car True 1347 | narrative epilogue False 1348 | neck scarf False 1349 | needle sew False 1350 | needle thread False 1351 | negotiating asking True 1352 | nervousness sweat False 1353 | nice mean False 1354 | niece nephew False 1355 | nod agreement True 1356 | noise crash False 1357 | noise silence False 1358 | normal crazy False 1359 | north south False 1360 | note symphony False 1361 | note song False 1362 | novel book True 1363 | novel foreword False 1364 | novice experience False 1365 | novice inexperience True 1366 | nun abbey False 1367 | nun chastity True 1368 | oak tree True 1369 | obese fat True 1370 | obese overeat True 1371 | obey protest False 1372 | object intangible False 1373 | object photo True 1374 | ocean seascape False 1375 | ocean water True 1376 | oceanography ocean True 1377 | ocean oceanography False 1378 | office telephone False 1379 | office working False 1380 | oil lubricant True 1381 | old youth False 1382 | omelette egg True 1383 | omniscient ignorant False 1384 | opera song True 1385 | option choice True 1386 | orchard apple True 1387 | order soldier True 1388 | organize cluttered False 1389 | original banal False 1390 | ounce pound False 1391 | out in False 1392 | oven kitchen False 1393 | overbearing caring True 1394 | own buy False 1395 | owner property False 1396 | pacific ocean True 1397 | pacifier infancy False 1398 | pacifist peace True 1399 | pack wolf True 1400 | page book False 1401 | page chapter False 1402 | page margin True 1403 | page paragraph True 1404 | page book False 1405 | pain agony False 1406 | pain blow False 1407 | pain medicate False 1408 | painful sunburn False 1409 | paint artistic True 1410 | paint brush False 1411 | paint picture False 1412 | paint wall False 1413 | painter portrait False 1414 | painting sketch True 1415 | palomino horse True 1416 | pane glass True 1417 | panic fear True 1418 | pant clothes True 1419 | pant trouser True 1420 | paper flimsy True 1421 | paper margin True 1422 | paper money False 1423 | paper outline True 1424 | paragraph word True 1425 | parched dehydrate True 1426 | parched thirstiness True 1427 | parent hate False 1428 | parenthood pride False 1429 | parenthood worry False 1430 | parent baby False 1431 | parent child True 1432 | parishioner preach False 1433 | party alcohol True 1434 | party celebrant True 1435 | party guest True 1436 | passionate lust False 1437 | password access True 1438 | past history False 1439 | patient health False 1440 | pay debtor True 1441 | peace magnanimous False 1442 | peace war False 1443 | peeling cooking False 1444 | pen pencil False 1445 | pen writer False 1446 | pencil paper False 1447 | pencil pen False 1448 | pencil write False 1449 | penis woman False 1450 | penny coin True 1451 | penny quarter False 1452 | pensive thought True 1453 | pepper seasoning True 1454 | perform audience True 1455 | performance applause False 1456 | performance choreography True 1457 | permeable porous False 1458 | perplexed certain False 1459 | pessimist hope False 1460 | pest insecticide False 1461 | pharmacology drug True 1462 | pharmacy medicine True 1463 | phd doctor False 1464 | phone battery False 1465 | photo landscape True 1466 | photo object False 1467 | photograph event True 1468 | photograph frame True 1469 | photograph image True 1470 | piano instrument True 1471 | picnic snack True 1472 | picture drawing False 1473 | picture frame True 1474 | picture image True 1475 | pie crust True 1476 | pie slice True 1477 | pig animal True 1478 | pillow soft True 1479 | pimple face True 1480 | pimple skin True 1481 | pitch baseball False 1482 | pitch windup False 1483 | pitcher baseball False 1484 | pitching baseball False 1485 | pizza cheesy True 1486 | pizza slice True 1487 | plain flat True 1488 | planet earth False 1489 | planet space False 1490 | plant seed False 1491 | plant botany False 1492 | plastic polymer True 1493 | plate dish True 1494 | plate china True 1495 | play act True 1496 | play enjoy False 1497 | play musician False 1498 | play solemnly False 1499 | playbook football False 1500 | player game False 1501 | player team False 1502 | playground slide False 1503 | pleasant agonizing False 1504 | pliable bend False 1505 | plump thinness False 1506 | pod whale True 1507 | poem verse True 1508 | poem sonnet False 1509 | poison die True 1510 | poison feed True 1511 | police gun False 1512 | poodle dog True 1513 | pool water True 1514 | poor money False 1515 | pop fizzy True 1516 | porch house True 1517 | porpoise mammal True 1518 | posse purchase False 1519 | postscript letter False 1520 | pot kitchen False 1521 | pot vessel True 1522 | potholder kitchen False 1523 | pound ounce True 1524 | praying church False 1525 | preach disciple True 1526 | preach parishioner True 1527 | pregnancy baby True 1528 | pregnancy development False 1529 | preoperative operation False 1530 | preparation disaster False 1531 | preschool kindergarten False 1532 | present christmas False 1533 | preservative salt False 1534 | press book True 1535 | pressed iron False 1536 | pretty beautiful True 1537 | pretty ugly False 1538 | preview movie False 1539 | previously subsequently False 1540 | price inflation False 1541 | price sell False 1542 | pride lion True 1543 | priest holy True 1544 | princess tiara False 1545 | prison criminal True 1546 | prisoner punishment True 1547 | professional amateur False 1548 | professor intellectual True 1549 | professor student True 1550 | profile face True 1551 | profligate degeneracy True 1552 | program code True 1553 | programmer computer False 1554 | progressive stagnant False 1555 | promote advertise False 1556 | promotion raise False 1557 | proprietor employee True 1558 | prosperity slum False 1559 | prostitute virginity False 1560 | protest obey False 1561 | provocative controversy True 1562 | psychotic insanity True 1563 | publishing writing True 1564 | punch hatred True 1565 | punch pain True 1566 | punish spank False 1567 | punishment prisoner False 1568 | purling knitting False 1569 | push shove False 1570 | quarter penny True 1571 | question answer True 1572 | question suspect True 1573 | quick fast False 1574 | quilt square True 1575 | rabbit hop False 1576 | raccoon animal True 1577 | rage happiness False 1578 | rage irritation True 1579 | rain dryness False 1580 | rain storm True 1581 | rain weather True 1582 | rainbow monochromatic False 1583 | raise child True 1584 | raise elevate True 1585 | raise salary True 1586 | ranger team True 1587 | rape fuck True 1588 | raw cooked False 1589 | read learn False 1590 | reaping harvest False 1591 | recipe ingredient True 1592 | record cassette False 1593 | recording sound True 1594 | red color True 1595 | red stop True 1596 | referee game False 1597 | referee whistle False 1598 | refinery gas True 1599 | refinery oil True 1600 | refrigerator appliance True 1601 | refrigerator food True 1602 | reject accept False 1603 | relaxing working False 1604 | release captive False 1605 | relief tylenol False 1606 | remote button True 1607 | remote television False 1608 | remote tv False 1609 | repair break False 1610 | repair broken False 1611 | reparable fixed False 1612 | repel attract False 1613 | repetition boredom True 1614 | repine cheerful False 1615 | replica artwork True 1616 | request beg False 1617 | resistant conquer False 1618 | resistant stop False 1619 | response stimulus False 1620 | rest restorative True 1621 | rest sick False 1622 | restaurant chef True 1623 | restaurant food True 1624 | restaurant meal True 1625 | restfulness sleep False 1626 | restroom bathroom True 1627 | retiree job False 1628 | revived dead False 1629 | rich poor False 1630 | ridicule tease True 1631 | rim cup True 1632 | ring jewelry True 1633 | ring wedding False 1634 | ring jewelry True 1635 | rise sink False 1636 | rise tide True 1637 | rivalry serenity False 1638 | river bank True 1639 | river bed True 1640 | river delta True 1641 | riverbed water False 1642 | road ditch True 1643 | robin bird True 1644 | rodent mouse False 1645 | roll round False 1646 | roof shingle True 1647 | room curtain False 1648 | room house False 1649 | room wall True 1650 | root tree False 1651 | root bush False 1652 | rose florist False 1653 | rough sand False 1654 | rough smooth False 1655 | route direction True 1656 | route map True 1657 | routine agenda True 1658 | royalty crown False 1659 | run exercise False 1660 | run fast True 1661 | run jog False 1662 | run lethargic False 1663 | run sprint True 1664 | run sweat True 1665 | run-on sentence True 1666 | runner finish False 1667 | running fast True 1668 | sad cry False 1669 | sad cry False 1670 | sad depressed True 1671 | sad depression True 1672 | sad happy False 1673 | sad smiling False 1674 | sadness cry False 1675 | sadness despair False 1676 | sadness melancholia False 1677 | safe valuable True 1678 | saint holiness True 1679 | saint hell False 1680 | salesperson customer False 1681 | salmon fish True 1682 | salt flavor True 1683 | salt preservative True 1684 | sand beach False 1685 | sand rough False 1686 | sand smooth True 1687 | sandal shoe True 1688 | sandpaper smooth True 1689 | satiety hungry False 1690 | satisfaction eat False 1691 | satisfied starving False 1692 | saturated wet True 1693 | saturation hue True 1694 | saving miser False 1695 | scalpel surgeon False 1696 | scandal reputation True 1697 | scar beauty True 1698 | scar complexion True 1699 | scarce bounty False 1700 | scene act False 1701 | scholar book True 1702 | scholar intelligence True 1703 | school child True 1704 | school classroom False 1705 | school education True 1706 | school fish True 1707 | school learning True 1708 | school student True 1709 | school student True 1710 | scientist grant False 1711 | scratch cd True 1712 | scream angry True 1713 | scream terror True 1714 | screaming terror True 1715 | screw screwdriver False 1716 | screwdriver tool True 1717 | sculpture art True 1718 | sculpture artwork True 1719 | sculpture sculptor False 1720 | seamstress dress False 1721 | searing roasting False 1722 | seascape ocean True 1723 | seat stool False 1724 | second hour False 1725 | sedan coupe False 1726 | sediment silt False 1727 | seed plant False 1728 | selfish egotism False 1729 | sell buyer True 1730 | sell customer True 1731 | sell price True 1732 | seller customer False 1733 | senate senator True 1734 | senator politician True 1735 | senator senate False 1736 | senescence cane False 1737 | senescence wheelchair False 1738 | sensitivity boorish False 1739 | sentence criminal True 1740 | sentence run-on False 1741 | serenity rivalry False 1742 | serve customer True 1743 | sew needle False 1744 | sew rip False 1745 | sewing stitching True 1746 | sewn fabric False 1747 | sex pregnancy True 1748 | shadow object True 1749 | shaken sturdy False 1750 | shaking fear True 1751 | shampooing bathing False 1752 | sharpen dull False 1753 | sheet bedding True 1754 | sheet bedding True 1755 | shelf wall True 1756 | shine burnish False 1757 | shine dimly False 1758 | shine sun False 1759 | ship boat True 1760 | ship deck True 1761 | shirt blouse False 1762 | shirt clothing True 1763 | shirt garment True 1764 | shirt thread False 1765 | shirt clothes True 1766 | shirt clothing True 1767 | shoe boot False 1768 | shoe foot False 1769 | shoe sole True 1770 | shooter gun False 1771 | shopper sold False 1772 | shopping mall False 1773 | shop mall False 1774 | shore lake True 1775 | shore sea True 1776 | shorten distance True 1777 | shorten hem True 1778 | shout whisper False 1779 | shove push True 1780 | shovel dig False 1781 | shovel spoon False 1782 | shoving nudging True 1783 | showering cleanliness True 1784 | showering soaping True 1785 | shriek panic True 1786 | shy initiate False 1787 | sick cured False 1788 | sidewalk crack False 1789 | sidewalk yard True 1790 | sift separated True 1791 | sigh exhaustion True 1792 | sign direction True 1793 | signature acknowledgement True 1794 | silence noise True 1795 | sill window True 1796 | simple hard False 1797 | sin virtue True 1798 | sing musical True 1799 | singer microphone False 1800 | sink dense False 1801 | sin jesus False 1802 | skeptical persuade False 1803 | sketch image True 1804 | sketch painting False 1805 | skin blemish False 1806 | skin pimple False 1807 | skinny fat False 1808 | skirt garment True 1809 | skirt hem True 1810 | sky ceiling False 1811 | slap anger True 1812 | slay dragon False 1813 | sleep alertly False 1814 | sleep awake False 1815 | sleep doze True 1816 | sleep lay False 1817 | sleep restful True 1818 | sleep restfulness True 1819 | sleeplessness parenthood False 1820 | slide playground False 1821 | sloppy messy True 1822 | slow fast False 1823 | slow speed False 1824 | slowly run False 1825 | slowly sprint False 1826 | slurp drink True 1827 | small majority False 1828 | smart dumb False 1829 | smash flat True 1830 | smile angry False 1831 | smile friendship True 1832 | smile happiness True 1833 | smile sneer False 1834 | smile unhappiness True 1835 | smiling happy True 1836 | smiling sad False 1837 | smoke cigarette False 1838 | smoke fire True 1839 | snack picnic False 1840 | snake cobra False 1841 | snake worm False 1842 | snarl anger True 1843 | sneer smile True 1844 | snow cold True 1845 | snow shovel False 1846 | soap dish False 1847 | sobbing cry True 1848 | sober intoxicated False 1849 | sock clothing True 1850 | sock thread True 1851 | soda beverage True 1852 | sofa couch True 1853 | soft brittle False 1854 | soft rough False 1855 | soften voice True 1856 | sold shopper True 1857 | soldier gun False 1858 | soldier war True 1859 | soldier army False 1860 | sole shoe False 1861 | solid cement False 1862 | solid gaseous False 1863 | solution equation True 1864 | sombrero hat True 1865 | song emotion True 1866 | song note True 1867 | song opera False 1868 | songwriter lyric True 1869 | sonnet poem True 1870 | soothing gentle True 1871 | sorrow happiness False 1872 | sorrow tear False 1873 | sound song True 1874 | soup spoonful True 1875 | space planet True 1876 | spank punish False 1877 | spear weapon True 1878 | spectacle glass True 1879 | speed movement True 1880 | speed slow False 1881 | speed slowly False 1882 | speeder ticket False 1883 | spin twirl True 1884 | spinach vegetable True 1885 | spoon shovel False 1886 | spoon silverware True 1887 | spoon utensil True 1888 | sport ball False 1889 | spring breeze False 1890 | sprint fast True 1891 | sprint run True 1892 | sprint slowly False 1893 | squeezed soft False 1894 | stab wound True 1895 | stadium sport False 1896 | stair ladder False 1897 | stalk visit True 1898 | stalking attraction True 1899 | star brightness True 1900 | star space True 1901 | start finish False 1902 | starvation hunger True 1903 | starving hunger True 1904 | state city True 1905 | state county True 1906 | steadily stutter False 1907 | steal policeman False 1908 | steal take True 1909 | steel strength True 1910 | steel strong True 1911 | steel tough True 1912 | step dance False 1913 | steroid muscle True 1914 | stethoscope doctor False 1915 | stimulus response True 1916 | stink rotten False 1917 | stirring cooking False 1918 | stitch cloth False 1919 | stool seat True 1920 | stop resistant False 1921 | store product True 1922 | store shopper True 1923 | store shopping False 1924 | storm thunder False 1925 | stream bank True 1926 | strength steel False 1927 | stress headache True 1928 | stretched elastic False 1929 | strong steel False 1930 | structure weakness False 1931 | student dorm False 1932 | student essay False 1933 | student school False 1934 | student teacher False 1935 | student school False 1936 | student teacher True 1937 | studio art True 1938 | study learning True 1939 | studying library False 1940 | stupid intelligence False 1941 | sturdy break False 1942 | stutter speech True 1943 | stutter steadily False 1944 | subordinate instruct False 1945 | suckle young True 1946 | suffering masochist False 1947 | summary book True 1948 | sun hot True 1949 | sun tan True 1950 | sunburn painful True 1951 | sunglass eye True 1952 | sunlight photosynthesis False 1953 | sunscreen burn False 1954 | superman hero True 1955 | supermarket aisle True 1956 | supermarket grocery True 1957 | survive healthy False 1958 | suspect question False 1959 | swaddle infancy False 1960 | swan bird True 1961 | sweat heat False 1962 | sweat workout False 1963 | sweater wool True 1964 | sweating odor True 1965 | sweet candy True 1966 | swilling drinking True 1967 | swim fish False 1968 | sword knife False 1969 | symphony movement True 1970 | symphony note True 1971 | table desk False 1972 | table wood True 1973 | tail dog False 1974 | tail frog False 1975 | taint poisoned True 1976 | take borrow True 1977 | take steal False 1978 | talkative taciturn False 1979 | tea beverage True 1980 | teach educated True 1981 | teach ignorant False 1982 | teach instruct True 1983 | teacher certificate False 1984 | teacher student False 1985 | teacher student True 1986 | teacher college False 1987 | team player True 1988 | team player True 1989 | tear pantyhose True 1990 | tear sadness True 1991 | tear sorrow True 1992 | tear tragedy False 1993 | tedious monotonous True 1994 | teeth brush False 1995 | teeth retainer False 1996 | teeth toothbrush False 1997 | television electricity False 1998 | tennis volleying True 1999 | tent house False 2000 | terror fear True 2001 | thawed freeze False 2002 | theater play True 2003 | theft lock False 2004 | therapy talking True 2005 | thin chubby False 2006 | thirst drink False 2007 | thirstiness parched False 2008 | thought pensive False 2009 | thoughtful contemplation True 2010 | threaten warn True 2011 | thunder lightning True 2012 | thunder storm True 2013 | tiara princess False 2014 | tide rise False 2015 | tidy clean True 2016 | tip waiter False 2017 | tired exhaustion True 2018 | tiredness rest False 2019 | title story False 2020 | toddler infant False 2021 | tool screwdriver False 2022 | toothbrush teeth False 2023 | top bottom False 2024 | topography map True 2025 | topography map True 2026 | torture pain True 2027 | touch grope False 2028 | touch reach False 2029 | tragedy tear True 2030 | trailer wagon False 2031 | tranquil impatient False 2032 | transparent opaque False 2033 | transportation automobile False 2034 | trap bush False 2035 | treat patient True 2036 | treatment patient False 2037 | tree bark True 2038 | tree branch True 2039 | tree root True 2040 | tree sapling False 2041 | tree seedling False 2042 | trim shorten False 2043 | trim tree True 2044 | troop soldier True 2045 | trophy achievement True 2046 | trophy champion False 2047 | trophy team False 2048 | trophy winner False 2049 | trouser pant True 2050 | trout fish True 2051 | trowel gardener False 2052 | truck driver False 2053 | tryst flirtation False 2054 | tumor body True 2055 | twirl spin True 2056 | twist sinuous True 2057 | tycoon wealthy True 2058 | tylenol relief True 2059 | tyranny freedom False 2060 | ugly beautiful False 2061 | ugly hideous True 2062 | under over False 2063 | understand infant False 2064 | understanding hearing True 2065 | understood incomprehensible False 2066 | university school True 2067 | unkind insult False 2068 | unpardonable forgiven False 2069 | up down False 2070 | urban city True 2071 | use addict False 2072 | useable broken False 2073 | uterus baby True 2074 | vacation trip False 2075 | vacuum carpet False 2076 | valley mountain True 2077 | valuable safe False 2078 | van automobile True 2079 | vegetable carrot False 2080 | vegetarian hunt False 2081 | veil face True 2082 | vendor consumer True 2083 | victory strategy True 2084 | villain evil True 2085 | vintner wine True 2086 | violation citation False 2087 | violin instrument True 2088 | virgin purity True 2089 | virginia state True 2090 | virginity sex False 2091 | visit stalk False 2092 | volleyball bumping True 2093 | volleying tennis False 2094 | waiter tip False 2095 | walker antiquity False 2096 | wall baseboard True 2097 | wall brick True 2098 | wall ceiling True 2099 | wall floor True 2100 | wall hook False 2101 | wall paint False 2102 | wall room True 2103 | wall shelf True 2104 | wandering confused True 2105 | waning sunlight True 2106 | war destruction False 2107 | war peace False 2108 | war soldier False 2109 | war weapon False 2110 | warehouse box True 2111 | warm cool False 2112 | warmth coat False 2113 | warmth fire False 2114 | warmth heater False 2115 | warning trouble True 2116 | wash clean True 2117 | water beverage True 2118 | water drought False 2119 | water hydration True 2120 | water plant False 2121 | water thirst False 2122 | water wet True 2123 | wave acknowledgement True 2124 | wave acknowledgment True 2125 | wave crash False 2126 | weak strong False 2127 | weak tough False 2128 | weakness structure True 2129 | wealth entrepreneur False 2130 | website internet True 2131 | wedding grief False 2132 | wedding marriage False 2133 | week day True 2134 | wellness doctor False 2135 | wheat bread True 2136 | wheelchair senescence False 2137 | whine complain True 2138 | white black False 2139 | whole broken False 2140 | whole halved False 2141 | wig hair True 2142 | window frame True 2143 | window sill True 2144 | windy calm False 2145 | wine alcohol True 2146 | wine beer False 2147 | wine vintner False 2148 | wing hospital False 2149 | wing bird False 2150 | winner award False 2151 | winner ribbon False 2152 | winner victory True 2153 | winter christmas False 2154 | winter holiday False 2155 | wire metal True 2156 | withdrawal timid True 2157 | withdrawn sociable False 2158 | withstood irresistible False 2159 | woman man False 2160 | womb baby True 2161 | wood fireplace False 2162 | word letter False 2163 | working office False 2164 | working relaxing False 2165 | workout sweat True 2166 | worthless vital False 2167 | wrapper package True 2168 | wrapping taping True 2169 | wrinkle age True 2170 | wrinkle makeup False 2171 | wrist bracelet False 2172 | write paper False 2173 | writer pen False 2174 | wrong good False 2175 | yale university True 2176 | yard sidewalk True 2177 | yarmulke piety True 2178 | yarn spinner False 2179 | yawn boredom True 2180 | yell anger True 2181 | yelling anger True 2182 | yellow caution True 2183 | yogurt milk True 2184 | young old False 2185 | zebra stripe True 2186 | zoo animal True 2187 | zoo animal True 2188 | zoo lion True 2189 | zoology animal True 2190 | -------------------------------------------------------------------------------- /fold.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import numpy as np 4 | 5 | def generate_folds_random(rng, data, n_folds): 6 | assignments = rng.randint(n_folds, size=len(data)) 7 | folds = [] 8 | for i in xrange(n_folds): 9 | testmask = (assignments == i) 10 | valmask = (assignments == (i + 1) % n_folds) 11 | trainmask = ~(testmask | valmask) 12 | folds.append((np.array(data.index[trainmask]), 13 | np.array(data.index[valmask]), 14 | np.array(data.index[testmask]))) 15 | return folds 16 | 17 | def generate_folds_lhs(rng, data, n_folds): 18 | # get unique words 19 | lhwords = list(set(data.word1)) 20 | # randomize the list 21 | rng.shuffle(lhwords) 22 | # split into n_folds roughly equal groups 23 | folds_index = [] 24 | for i in xrange(n_folds): 25 | folds_index.append(set(lhwords[i::n_folds])) 26 | 27 | # so now we've got 10 folds, based on the lhs. now we need 28 | # to make sure that we don't have vocab overlap! 29 | folds = [] 30 | for i in xrange(n_folds): 31 | idx = folds_index[i] 32 | vidx = folds_index[(i + 1) % n_folds] 33 | testmask = data.word1.apply(lambda x: x in idx) 34 | valmask = data.word1.apply(lambda x: x in vidx) 35 | 36 | testrhswords = set(data.word2[testmask]) 37 | # no words on rhs of test in rhs of train 38 | testrhsmask1 = data.word2.apply(lambda x: x in testrhswords) 39 | # no words in lhs of test in rhs of train 40 | testrhsmask2 = data.word2.apply(lambda x: x in idx) 41 | # no words in rhs of test in lhs of train 42 | testrhsmask3 = data.word1.apply(lambda x: x in testrhswords) 43 | 44 | valmask = valmask & ~(testmask | testrhsmask1 | testrhsmask2 | testrhsmask3) 45 | 46 | valrhswords = set(data.word2[valmask]) 47 | valrhsmask1 = data.word2.apply(lambda x: x in valrhswords) 48 | valrhsmask2 = data.word2.apply(lambda x: x in vidx) 49 | valrhsmask3 = data.word1.apply(lambda x: x in valrhswords) 50 | 51 | trainmask = ~(testmask | testrhsmask1 | testrhsmask2 | testrhsmask3 | 52 | valmask | valrhsmask1 | valrhsmask2 | valrhsmask3) 53 | 54 | #wasted = ~(trainmask | testmask) 55 | #print "wasted:", np.sum(wasted)/float(len(wasted)) 56 | 57 | trainvocab = set(data[trainmask].word1).union(set(data[trainmask].word2)) 58 | valvocab = set(data[valmask].word1).union(set(data[valmask].word2)) 59 | testvocab = set(data[testmask].word1).union(set(data[testmask].word2)) 60 | #assert len(trainvocab.intersection(valvocab)) == 0 61 | assert len(trainvocab.intersection(testvocab)) == 0 62 | assert len(valvocab.intersection(testvocab)) == 0 63 | 64 | folds.append((np.array(data.index[trainmask]), np.array(data.index[valmask]), np.array(data.index[testmask]))) 65 | 66 | all_seen = set() 67 | for train, val, test in folds: 68 | all_seen.update(test) 69 | 70 | assert len(all_seen) == len(data) 71 | 72 | return folds 73 | 74 | 75 | -------------------------------------------------------------------------------- /lexent.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import os 4 | import os.path 5 | import argparse 6 | import logging 7 | from collections import defaultdict 8 | 9 | import numpy as np 10 | import pandas as pd 11 | from sklearn import metrics 12 | from scipy.stats import linregress 13 | from sklearn.preprocessing import normalize 14 | from sklearn.grid_search import ParameterGrid 15 | 16 | from utdeftvs import load_numpy 17 | 18 | import fold 19 | import models 20 | 21 | from custom_classifiers import ThresholdClassifier, SuperTreeClassifier 22 | tc = ThresholdClassifier() 23 | 24 | N_FOLDS = 20 25 | 26 | # before anything else, configure the logger 27 | logger = logging.getLogger() 28 | handler = logging.StreamHandler() 29 | formatter = logging.Formatter("%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S") 30 | handler.setFormatter(formatter) 31 | logger.addHandler(handler) 32 | logger.setLevel(logging.DEBUG) 33 | 34 | def longest_vector_posmatch(search, space): 35 | if not hasattr(space, 'posless'): 36 | setattr(space, 'posless', defaultdict(dict)) 37 | for i, v in enumerate(space.vocab): 38 | sep = v.rindex('/') 39 | word, pos = v[:sep], v[sep+1:] 40 | space.posless[word][pos] = space.magn[i] 41 | if search not in space.posless: 42 | return None 43 | options = space.posless[search] 44 | pos = max(options.keys(), key=options.__getitem__) 45 | return search + '/' + pos 46 | 47 | def always_nn_posmatch(search, space): 48 | return search + '/NN' 49 | 50 | best_pos_match = always_nn_posmatch 51 | #best_pos_match = longest_vector_posmatch 52 | 53 | def consolidate(list_of_dicts): 54 | """ 55 | Returns a dict of lists from a list of dicts 56 | """ 57 | consolidated = {} 58 | for k in list_of_dicts[0].keys(): 59 | consolidated[k] = np.array([d[k] for d in list_of_dicts]) 60 | return consolidated 61 | 62 | def feature_extraction(X, y, model, space, data): 63 | np.set_printoptions(precision=3, suppress=True) 64 | n_output = 10 65 | model.fit(X, y) 66 | data_vocab = set(list(data.word1) + list(data.word2)) 67 | D = space.matrix.shape[1] 68 | segments = model.coef_.shape[1] / D 69 | print "=== ORTHOG TEST ===" 70 | for s in xrange(segments): 71 | l = D*s 72 | r = D*(s+1) 73 | subset = normalize(model.coef_[:,l:r]) 74 | print subset.dot(subset.T) 75 | for coef_i in xrange(len(model.coef_)): 76 | print "=== COEF #%d ===" % coef_i 77 | full_magn = np.sum(np.square(model.coef_[coef_i])) 78 | for s in xrange(segments): 79 | l = D*s 80 | r = D*(s+1) 81 | feats = model.coef_[coef_i,l:r] 82 | p = np.sum(np.square(feats)) / full_magn 83 | print "Segment #%d [%d-%d] [%2.1f%%]" % (s + 1, l, r, 100*p) 84 | word_ranks = space.matrix.dot(feats) 85 | sorted = word_ranks.argsort() 86 | for i in xrange(n_output): 87 | fidx = sorted[-(i+1)] 88 | ridx = sorted[i] 89 | fscore = word_ranks[fidx] 90 | rscore = word_ranks[ridx] 91 | fword = space.vocab[fidx][:30] 92 | rword = space.vocab[ridx][:30] 93 | findata = (fword in data_vocab) and '*' or ' ' 94 | rindata = (rword in data_vocab) and '*' or ' ' 95 | print " %6.3f %s %-30s %6.3f %s %-30s" % (fscore, findata, fword, rscore, rindata, rword) 96 | print 97 | ctx_ranks = space.cmatrix.dot(feats) 98 | sorted = ctx_ranks.argsort() 99 | for i in xrange(n_output): 100 | fidx = sorted[-(i+1)] 101 | ridx = sorted[i] 102 | fscore = ctx_ranks[fidx] 103 | rscore = ctx_ranks[ridx] 104 | fctx = space.cvocab[fidx] 105 | rctx = space.cvocab[ridx] 106 | fword = fctx[fctx.rindex('+')+1:] 107 | rword = rctx[rctx.rindex('+')+1:] 108 | findata = (fword in data_vocab) and '*' or ' ' 109 | rindata = (rword in data_vocab) and '*' or ' ' 110 | print " %6.3f %s %-30s %6.3f %s %-30s" % (fscore, findata, fctx, rscore, rindata, rctx) 111 | 112 | def render_confusion_matrix(y_true, y_pred, labels): 113 | cm = metrics.confusion_matrix(y_true, y_pred) / float(len(y_true)) 114 | output = [] 115 | shortlabels = "abcdefghij" 116 | output += [" " + " ".join(a for a, b in zip(shortlabels, labels)) + " <- predicted as"] 117 | f = lambda v: ("%.2f" % v).lstrip("0").replace(".00", ". ") 118 | for i, (s, r) in enumerate(zip(shortlabels, labels)): 119 | output += [" " + " ".join(f(v) for v in cm[i]) + " | %s = %s" % (s, r)] 120 | return "\n".join(output) 121 | 122 | 123 | def standard_experiment(data, X, y, model, hyper, args): 124 | # data with predictions 125 | dwp = data.copy() 126 | 127 | seed = 1 128 | logger.debug(" On seed: %d / %d" % (seed, 20)) 129 | logger.debug(" Genenerating: %d folds" % N_FOLDS) 130 | rng = np.random.RandomState(seed) 131 | fold_key = 'fold_%02d' % seed 132 | pred_key = 'prediction_%02d' % seed 133 | pred_prob_key = 'probability_%02d' % seed 134 | 135 | # need our folds for cross validation 136 | folds = fold.generate_folds_lhs(rng, data, n_folds=N_FOLDS) 137 | train_sizes = np.array([len(f[0]) for f in folds], dtype=np.float) 138 | val_sizes = np.array([len(f[1]) for f in folds], dtype=np.float) 139 | test_sizes = np.array([len(f[2]) for f in folds], dtype=np.float) 140 | 141 | logger.debug(" Train sizes: %.1f" % np.mean(train_sizes)) 142 | logger.debug(" Val sizes: %.1f" % np.mean(val_sizes)) 143 | logger.debug(" Test sizes: %.1f" % np.mean(test_sizes)) 144 | logger.debug(" Test-Tr ratio: %.1f%%" % np.mean(test_sizes*100./(train_sizes + test_sizes))) 145 | logger.debug(" Percent data: %.1f%%" % np.mean((train_sizes + test_sizes)*100./len(y))) 146 | 147 | # perform cross validation 148 | 149 | pooled_eval, predictions, cv_scores = cv_trials(X, y, folds, model, hyper) 150 | dwp['prediction'] = predictions['pred'] 151 | dwp['foldno'] = predictions['foldno'] 152 | dwp['correct'] = (dwp['prediction'] == dwp['label']) 153 | 154 | for i, v in enumerate(cv_scores['f1']): 155 | logger.info(" Fold %02d F1: %.3f" % (i + 1, v)) 156 | 157 | logger.info("\nConfusion matrix:\n" + render_confusion_matrix(y, predictions['pred'], labels=data.label.cat.categories)) 158 | 159 | for k in cv_scores.keys(): 160 | mu = cv_scores[k].mean() 161 | sigma = cv_scores[k].std() 162 | logger.info(" %3s across CV: %.3f %.3f" % (k.upper(), mu, sigma)) 163 | logger.debug("") 164 | 165 | if args.output: 166 | dwp.to_csv("%s/exp:%s,data:%s,space:%s,model:%s.csv.bz2" % ( 167 | args.output, args.experiment, args.data, 168 | os.path.basename(args.space), 169 | args.model 170 | ), index=False, compression='bz2') 171 | 172 | def cv_trials(X, y, folds, model, hyper): 173 | N = len(y) 174 | 175 | cv_scores = [] 176 | predictions = { 177 | 'pred': np.zeros(N, dtype=np.bool), 178 | 'proba': np.zeros(N), 179 | 'foldno': np.zeros(N, dtype=np.int32) - 1, 180 | } 181 | pg = list(ParameterGrid(hyper)) 182 | for foldno, (train, val, test) in enumerate(folds): 183 | train_X, train_y = X[train], y[train] 184 | val_X, val_y = X[val], y[val] 185 | test_X, test_y = X[test], y[test] 186 | best_params = None 187 | best_val_f1 = None 188 | for these_params in pg: 189 | model.set_params(**these_params) 190 | model.fit(train_X, train_y) 191 | this_val_f1 = metrics.f1_score(val_y, model.predict(val_X), average="weighted") 192 | if not best_params or this_val_f1 > best_val_f1: 193 | best_params = these_params 194 | best_val_f1 = this_val_f1 195 | if len(pg) > 1: 196 | model.set_params(**best_params) 197 | model.fit(train_X, train_y) 198 | train_f1 = metrics.f1_score(train_y, model.predict(train_X), average="weighted") 199 | 200 | preds_y = model.predict(test_X) 201 | predictions['pred'][test] = preds_y 202 | 203 | predictions['foldno'][test] = foldno 204 | 205 | fold_eval = {'f1': metrics.f1_score(test_y, preds_y, average="weighted"), 206 | 'p': metrics.precision_score(test_y, preds_y, average="weighted"), 207 | 'r': metrics.recall_score(test_y, preds_y, average="weighted"), 208 | 'a': metrics.accuracy_score(test_y, preds_y)} 209 | print "[%02d] Best hyper [train %.3f -> val %.3f -> test %.3f] %s" % (foldno, train_f1, best_val_f1, fold_eval['f1'], best_params) 210 | 211 | 212 | cv_scores.append(fold_eval) 213 | np.set_printoptions(suppress=True) 214 | 215 | # now we want to compute global evaluations, and consolidate metrics 216 | cv_scores = consolidate(cv_scores) 217 | 218 | preds_y = predictions['pred'] 219 | pooled_eval = {'f1': metrics.f1_score(y, preds_y, average="weighted"), 220 | 'p': metrics.precision_score(y, preds_y, average="weighted"), 221 | 'r': metrics.recall_score(y, preds_y, average="weighted"), 222 | 'a': metrics.accuracy_score(y, preds_y)} 223 | 224 | return pooled_eval, predictions, cv_scores 225 | 226 | def load_data(filename, space): 227 | data = pd.read_table(filename) 228 | data['word1'] = data['word1'].apply(lambda x: best_pos_match(x, space)) 229 | data['word2'] = data['word2'].apply(lambda x: best_pos_match(x, space)) 230 | 231 | mask1 = data.word1.apply(lambda x: x in space.lookup) 232 | mask2 = data.word2.apply(lambda x: x in space.lookup) 233 | 234 | T = len(data) 235 | M1T = np.sum(mask1) 236 | M2T = np.sum(mask2) 237 | data = data[mask1 & mask2].reset_index(drop=True) 238 | F = len(data) 239 | logger.debug("") 240 | logger.debug(" Data Filename: %s" % filename) 241 | logger.debug(" Total Data: %5d" % T) 242 | logger.debug(" LHS OOV: %5d ( %4.1f%% )" % (M1T, M1T*100./T)) 243 | logger.debug(" RHS OOV: %5d ( %4.1f%% )" % (M2T, M2T*100./T)) 244 | logger.debug(" Final: %5d ( %4.1f%% )" % (F, F*100./T)) 245 | logger.debug("") 246 | 247 | if data.label.dtype != bool: 248 | cats = list(set(data.label)) 249 | import ipdb; ipdb.set_trace() 250 | data['label'] = data.label.astype('category', categories=cats) 251 | 252 | return data 253 | 254 | 255 | 256 | 257 | def main(): 258 | # Argument parsing 259 | parser = argparse.ArgumentParser('Lexical Entailment Classifier') 260 | parser.add_argument('--data', '-d', help='Input file') 261 | parser.add_argument('--space', '-s', help='Distributional space') 262 | parser.add_argument('--model', '-m', help='Model setup', choices=models.SETUPS.keys()) 263 | parser.add_argument('--experiment', '-e', default='standard', choices=('standard', 'random', 'match_error', 'featext', 'strat', 'levy')) 264 | parser.add_argument('--stratifier') 265 | parser.add_argument('--output', '-o') 266 | args = parser.parse_args() 267 | 268 | logger.debug('Lexent Arguments: ') 269 | logger.debug(args) 270 | 271 | # Steps that are the same regardless of experiments 272 | logger.debug("Loading space") 273 | nn_space = load_numpy(args.space, insertblank=True) 274 | space = nn_space.normalize() 275 | 276 | # Handle vocabulary issues 277 | logger.debug("Reading data") 278 | data = load_data(args.data, space) 279 | 280 | logger.debug(" Model: %s" % args.model) 281 | model, features, hyper = models.load_setup(args.model) 282 | 283 | logger.debug(" Features: %s" % features) 284 | X, y = models.generate_feature_matrix(data, space, features) 285 | 286 | if args.experiment == 'standard': 287 | standard_experiment(data, X, y, model, hyper, args) 288 | elif args.experiment == 'featext': 289 | feature_extraction(X, y, model, space, data) 290 | 291 | 292 | 293 | 294 | 295 | if __name__ == '__main__': 296 | main() 297 | -------------------------------------------------------------------------------- /models.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import numpy as np 4 | from sklearn import svm, linear_model, dummy 5 | 6 | from custom_classifiers import ThresholdClassifier, ksim_kernel 7 | 8 | SETUPS = { 9 | # baseline most common 10 | 'baseline': ('baseline', 'cosine'), 11 | # baseline "unsupervised" 12 | 'cosine': ('threshold', 'cosine'), 13 | 14 | # baseline memorizations 15 | 'lhs': ('lr2', 'lhs'), 16 | 'rhs': ('lr2', 'rhs'), 17 | 'concat': ('linear', 'concat'), 18 | 'concat2': ('lr2', 'concat'), 19 | 20 | # asym models 21 | 'diff': ('linear', 'diff'), 22 | 'diffsq': ('linear', 'diffsq'), 23 | 24 | # asym lr 25 | 'diff1': ('lr1', 'diff'), 26 | 'diff2': ('lr2', 'diff'), 27 | 28 | # asym lr 29 | 'diffsq1': ('lr1', 'diffsq'), 30 | 'diffsq2': ('lr2', 'diffsq'), 31 | 32 | # rb models 33 | 'diffrbf': ('rbf', 'diff'), 34 | 'concatrbf': ('rbf', 'concat'), 35 | 'asymrbf': ('rbf', 'diffsq'), 36 | 37 | # other models 38 | 'bdsm': ('bdsm', 'concat'), 39 | 'stephen': ('stephen', 'concat'), 40 | 'ksim': ('ksim', 'concat'), 41 | 'sigmoid': ('sigmoid', 'concat'), 42 | 43 | 'concat+asym': ('lr2', 'concat+asym'), 44 | 'concat+diff': ('lr2', 'concat+diff'), 45 | 'concat+sq': ('lr2', 'concat+sq'), 46 | 'concat+cos': ('lr2', 'concat+cos'), 47 | 'concat+cosrbf': ('rbf', 'concat+cos'), 48 | 49 | 'super': ('super', 'concat'), 50 | 'super-cos': ('super-cos', 'concat'), 51 | 'super-incl': ('super-incl', 'concat'), 52 | 'super-proj': ('super-proj', 'concat'), 53 | 54 | 'sq': ('linear', 'sq'), 55 | 56 | # others I dont want now 57 | #('lhs', 'lr1', 'lhs'), 58 | #('rhs', 'lr1', 'rhs'), 59 | #('concat', 'lr1', 'concat'), 60 | #('diff', 'lr1', 'diff'), 61 | #('diffsq', 'lr1', 'diffsq'), 62 | 63 | #('lhs', 'lr2', 'lhs'), 64 | #('rhs', 'lr2', 'rhs'), 65 | #('concat', 'lr2', 'concat'), 66 | #('diff', 'lr2', 'diff'), 67 | #('diffsq', 'lr2', 'diffsq'), 68 | 69 | 'nn': ('nn', 'concat'), 70 | } 71 | 72 | def _lsplit(needle, haystack): 73 | i = haystack.index(needle) 74 | return haystack[:i], haystack[i+1:] 75 | 76 | def topk(matrix, k=10): 77 | return np.argsort(-matrix, 1)[:,:k] 78 | 79 | def find_indices(space, relation, candidates): 80 | tofind = (relation + '+' + space.vocab[c] for c in candidates) 81 | for f in tofind: 82 | i = space.clookup.get(f) 83 | if i: 84 | return i 85 | return 0 86 | 87 | def generate_relation_matrix(data, space): 88 | retval_l = [] 89 | retval_r = [] 90 | from collections import Counter 91 | relations = Counter([_lsplit('+', c)[0] for c in space.cvocab[1:]]) 92 | relations = [k for k, v in relations.iteritems() if v >= 10] 93 | setattr(space, 'relations', relations) 94 | 95 | k = 0 96 | for i, row in data.iterrows(): 97 | k = k + 1 98 | word1 = row['word1'] 99 | word2 = row['word2'] 100 | lhs = space.matrix[space.lookup[word1]] 101 | rhs = space.matrix[space.lookup[word2]] 102 | indices = [find_indices(space, r, [space.lookup[word2]]) for r in relations] 103 | ests_l = space.cmatrix[indices].dot(lhs) 104 | tofind = [(r + '+' + word1) for r in relations] 105 | indices = [find_indices(space, r, [space.lookup[word1]]) for r in relations] 106 | ests_r = space.cmatrix[indices].dot(rhs) 107 | retval_l.append(ests_l) 108 | retval_r.append(ests_r) 109 | retval = np.concatenate([np.array(retval_l), np.array(retval_r)], axis=1) 110 | retval = np.exp(retval) 111 | from sklearn.preprocessing import normalize 112 | return normalize(retval, norm='l2') 113 | return retval 114 | 115 | 116 | def words2matrix(dataseries, space): 117 | return np.array(list(dataseries.apply(lambda x: space[x]))) 118 | 119 | def generate_cosine_matrix(data, space): 120 | lhs = words2matrix(data.word1, space) 121 | rhs = words2matrix(data.word2, space) 122 | return np.array([np.sum(np.multiply(lhs, rhs), axis=1)]).T 123 | 124 | def generate_diff_matrix(data, space): 125 | lhs = words2matrix(data.word1, space) 126 | rhs = words2matrix(data.word2, space) 127 | 128 | # difference vector 129 | diff = rhs - lhs 130 | 131 | return diff 132 | 133 | def generate_diffsq_matrix(data, space): 134 | lhs = words2matrix(data.word1, space) 135 | rhs = words2matrix(data.word2, space) 136 | 137 | # difference vector 138 | diff = rhs - lhs 139 | # element wise squared diffs 140 | diff_sq = np.power(diff, 2) 141 | 142 | X = np.concatenate([diff, diff_sq], axis=1) 143 | return X 144 | 145 | def generate_concat_matrix(data, space): 146 | lhs = words2matrix(data.word1, space) 147 | rhs = words2matrix(data.word2, space) 148 | 149 | X = np.concatenate([lhs, rhs], axis=1) 150 | return X 151 | 152 | def generate_lhs_matrix(data, space): 153 | lhs = words2matrix(data.word1, space) 154 | return lhs 155 | 156 | def generate_rhs_matrix(data, space): 157 | rhs = words2matrix(data.word2, space) 158 | return rhs 159 | 160 | def bin(X, nbins=20): 161 | equa0 = (X <= 0.0) 162 | equa1 = (X >= 1.0) 163 | 164 | binned = [] 165 | 166 | groups = range(nbins+1) 167 | for g1, g2 in zip(groups, groups[1:]): 168 | l, u = g1/float(nbins), g2/float(nbins) 169 | binned.append((l < X) & (X <= u)) 170 | retval = np.concatenate([equa0, equa1] + binned, axis=1) 171 | return retval 172 | 173 | def generate_feature_matrix(data, space, features): 174 | if features == 'relation': 175 | X = generate_relation_matrix(data, space) 176 | elif features == 'cosine': 177 | X = generate_cosine_matrix(data, space) 178 | elif features == 'lhs': 179 | X = generate_lhs_matrix(data, space) 180 | elif features == 'rhs': 181 | X = generate_rhs_matrix(data, space) 182 | elif features == 'concat': 183 | X = generate_concat_matrix(data, space) 184 | elif features == 'diff': 185 | X = generate_diff_matrix(data, space) 186 | elif features == 'diffsq': 187 | X = generate_diffsq_matrix(data, space) 188 | elif features == 'concat+cos': 189 | X1 = generate_lhs_matrix(data, space) 190 | X2 = generate_rhs_matrix(data, space) 191 | X3 = generate_cosine_matrix(data, space) 192 | X = np.concatenate([X1, X2, X3, bin(X3)], axis=1) 193 | elif features == 'sq': 194 | X = np.square(generate_diff_matrix(data, space)) 195 | elif features == 'concat+diff': 196 | X1 = generate_diff_matrix(data, space) 197 | X2 = generate_lhs_matrix(data, space) 198 | X3 = generate_rhs_matrix(data, space) 199 | X = np.concatenate([X1, X2, X3], axis=1) 200 | elif features == 'concat+asym': 201 | X1 = generate_diff_matrix(data, space) 202 | X2 = generate_lhs_matrix(data, space) 203 | X3 = generate_rhs_matrix(data, space) 204 | X4 = np.square(X1) 205 | X = np.concatenate([X1, X2, X3, X4], axis=1) 206 | elif features == 'concat+sq': 207 | X1 = np.square(generate_diff_matrix(data, space)) 208 | X2 = generate_lhs_matrix(data, space) 209 | X3 = generate_rhs_matrix(data, space) 210 | X = np.concatenate([X1, X2, X3], axis=1) 211 | elif features == 'diffrhs': 212 | X1 = generate_diffsq_matrix(data, space) 213 | X2 = generate_rhs_matrix(data, space) 214 | X = np.concatenate([X1, X2], axis=1) 215 | else: 216 | raise ValueError("Can't generate %s features" % features) 217 | if data.label.dtype == bool: 218 | y = data.label.as_matrix().astype('int32') 219 | else: 220 | y = data.label.cat.codes.as_matrix().astype('int32') 221 | return X, y 222 | 223 | def dict_union(a, b): 224 | c = {} 225 | for k, v in a.iteritems(): 226 | c[k] = v 227 | for k, v in b.iteritems(): 228 | c[k] = v 229 | return c 230 | 231 | def classifier_factory(name): 232 | Cs = {'C': [1e+0, 1e-1, 1e+1, 1e-2, 1e+2, 1e-3, 1e+3], 'class_weight': ['balanced']} 233 | if name == 'linear': 234 | return svm.LinearSVC(dual=False), Cs 235 | elif name == 'poly': 236 | return svm.SVC(kernel='poly', degree=3, shrinking=False, cache_size=8192, max_iter=2000), Cs 237 | elif name == 'threshold': 238 | return ThresholdClassifier(), {} 239 | elif name == 'rbf': 240 | return svm.SVC(kernel='rbf', class_weight='balanced', cache_size=8192, shrinking=False, max_iter=2000, C=1e+2), Cs 241 | elif name == 'lr2': 242 | return linear_model.LogisticRegression(penalty='l2', solver='liblinear'), Cs 243 | elif name == 'lr1': 244 | return linear_model.LogisticRegression(penalty='l1', solver='liblinear'), Cs 245 | elif name == 'baseline': 246 | return dummy.DummyClassifier(strategy='most_frequent'), {} 247 | elif name == 'nn': 248 | import nn 249 | return nn.MirrorClassifier(), {} 250 | elif name.startswith('super'): 251 | from custom_classifiers import SuperTreeClassifier 252 | remove = name[6:] 253 | extra = {} 254 | if remove: 255 | extra[remove] = False 256 | return SuperTreeClassifier(**extra), dict_union(Cs, {'n_features': [1, 2, 3, 4, 5, 6]}) 257 | elif name == 'ksim': 258 | return svm.SVC(kernel=ksim_kernel, cache_size=8192, shrinking=False, max_iter=2000), Cs 259 | else: 260 | raise ValueError("Don't know about %s models." % name) 261 | 262 | def load_setup(setupname): 263 | kl, fe = SETUPS[setupname] 264 | cl, hyper = classifier_factory(kl) 265 | return cl, fe, hyper 266 | -------------------------------------------------------------------------------- /nn.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | import numpy as np 4 | import tensorflow as tf 5 | from sklearn.base import BaseEstimator, ClassifierMixin 6 | from sklearn.utils.class_weight import compute_class_weight 7 | from sklearn.utils import shuffle 8 | 9 | 10 | BATCH_SIZE = 32 11 | DROPOUT = 0.5 12 | EPOCHS = 25 13 | LEARNING_RATE = 0.1 14 | MOMENTUM_RATE = 0.9 15 | REG_RATE = 0.0 16 | 17 | def glorot(shape): 18 | v = np.sqrt(6./np.sum(shape)) 19 | return tf.random_uniform(shape, -v, v) 20 | 21 | class MirrorClassifier(BaseEstimator, ClassifierMixin): 22 | sess = None 23 | 24 | def __init__(self, k=300, n_features=50): 25 | self.k = k 26 | self.n = n_features 27 | 28 | def _number_outputs(self, labels): 29 | if labels.max() == 1: 30 | return 1 31 | else: 32 | return labels.max() + 1 33 | 34 | def _setup(self): 35 | if self.sess: 36 | self.sess.close() 37 | self.sess = None 38 | 39 | self.X_ = tf.placeholder(tf.float32, shape=[None, self.k * 2], name="vectors") 40 | self.Y_ = tf.placeholder(tf.int32, [None], name="labels") 41 | self.dropout_ = tf.placeholder(tf.float32, [], name="dropout") 42 | self.weights_ = tf.placeholder(tf.float32, [None, 1], name="weights") 43 | 44 | left0 = self.X_[:,:self.k] 45 | rite0 = self.X_[:,self.k:] 46 | 47 | self.W1 = tf.Variable(glorot([self.k, self.n]), name="W1") 48 | self.W1do = tf.nn.dropout(self.W1, keep_prob=(1. - self.dropout_)) 49 | left1 = tf.nn.relu(tf.matmul(left0, self.W1do)) 50 | rite1 = tf.nn.relu(tf.matmul(rite0, self.W1do)) 51 | incl = left1 - rite1 52 | sims = tf.reduce_sum(tf.mul(left0, rite0), 1, True) 53 | layer1 = tf.concat(1, [left1, rite1]) 54 | h = layer1.get_shape()[1].value 55 | 56 | self.W2 = tf.Variable(glorot([h, h]), name="W2") 57 | self.B2 = tf.Variable(tf.zeros(h), name="bias2") 58 | self.W2do = tf.nn.dropout(self.W2, keep_prob=(1. - self.dropout_)) 59 | layer2 = (tf.nn.bias_add(tf.matmul(layer1, self.W2do), self.B2)) 60 | 61 | #self.W3 = tf.Variable(glorot([h, self.o]), name="W2") 62 | #self.W3do = tf.nn.dropout(self.W3, keep_prob=(1. - self.dropout_)) 63 | #self.B3 = tf.Variable(tf.zeros(self.o), name="bias3") 64 | #layer3 = (tf.nn.bias_add(tf.matmul(layer2, self.W3do), self.B3)) 65 | 66 | self.output = layer2 67 | if self.o == 1: 68 | self.probas = tf.nn.sigmoid(self.output) 69 | self.obj = tf.nn.sigmoid_cross_entropy_with_logits(tf.reshape(self.output, [-1]), tf.to_int32(self.Y_)) 70 | else: 71 | self.probas = tf.nn.softmax(self.output) 72 | self.obj = tf.nn.sparse_softmax_cross_entropy_with_logits(self.output, self.Y_) 73 | self.obj = tf.reduce_mean(tf.mul(self.weights_, self.obj)) 74 | #self.opt = tf.train.MomentumOptimizer(LEARNING_RATE, MOMENTUM_RATE).minimize(self.obj) 75 | self.opt = tf.train.AdamOptimizer().minimize(self.obj) 76 | 77 | self.sess = tf.Session() 78 | 79 | @property 80 | def coef_(self): 81 | if self.sess: 82 | return self.sess.run(self.W1).T 83 | return None 84 | 85 | def fit(self, X, y): 86 | if not (self.sess and self._number_outputs(y) == self.o): 87 | self.o = self._number_outputs(y) 88 | self._setup() 89 | 90 | self.sess.run(tf.initialize_all_variables()) 91 | 92 | weights = compute_class_weight('balanced', np.arange(y.max() + 1), y)[y.astype(np.int32)].reshape(-1, 1) 93 | X = X.astype(np.float32) 94 | full_data_fd = { 95 | self.X_: X, 96 | self.Y_: y, 97 | self.weights_: weights, 98 | self.dropout_: 0.0, 99 | } 100 | for epoch in xrange(1, EPOCHS+1): 101 | X, y, weights = shuffle(X, y, weights) 102 | for mb in xrange(len(X) / BATCH_SIZE): 103 | i, j = mb * BATCH_SIZE, max(len(X), (mb + 1) * BATCH_SIZE) 104 | fd = { 105 | self.X_: X[i:j], 106 | self.Y_: y[i:j], 107 | self.weights_: weights[i:j], 108 | self.dropout_: DROPOUT, 109 | } 110 | _ = self.sess.run([self.obj, self.opt], fd) 111 | loss = self.sess.run(self.obj, full_data_fd) 112 | print "%4d loss: %.3f" % (epoch, loss) 113 | return self 114 | 115 | def predict_proba(self, X): 116 | fd = {self.X_: X.astype(np.float32), self.dropout_: 0.0} 117 | return self.sess.run(self.probas, fd) 118 | 119 | def predict(self, X): 120 | if self.o == 1: 121 | return self.predict_proba(X) >= 0.5 122 | else: 123 | return self.predict_proba(X).argmax(axis=1) 124 | 125 | def set_params(self, **kwargs): 126 | # todo, uninialize the model 127 | pass 128 | 129 | -------------------------------------------------------------------------------- /scripts/collect.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import sys 3 | import argparse 4 | import numpy as np 5 | import pandas as pd 6 | 7 | ignore = set([ 8 | 'training set sizes', 9 | 'testing set sizes', 10 | 'test as % of train', 11 | 'Standard Classification', 12 | 'always', 13 | 'lhs', 14 | 'rhs', 15 | ]) 16 | 17 | def parse_item(lines): 18 | # contains online lines between SPACE: and the ending trial 19 | space = '' 20 | data = '' 21 | for line in lines: 22 | if 'SPACE:' in line: 23 | space = line.split()[-1] 24 | elif 'DATA:' in line: 25 | data = line.split()[-1] 26 | else: 27 | model, feats, f1, lower, leq1, mean, leq2, upper = line.split() 28 | yield dict(space=space, data=data, model=model + "_" + feats, 29 | lower=float(lower), upper=float(upper), mean=float(mean)) 30 | 31 | 32 | 33 | def parse_items(lines): 34 | grouped = [] 35 | for line in lines: 36 | if 'SPACE:' in line: 37 | if grouped: 38 | for i in parse_item(grouped): yield i 39 | grouped = [] 40 | grouped.append(line) 41 | if grouped: 42 | for i in parse_item(grouped): yield i 43 | 44 | 45 | def main(): 46 | parser = argparse.ArgumentParser('Collects results neatly') 47 | parser.add_argument('--input', '-i', default='results.log') 48 | parser.add_argument('--space', '-s') 49 | parser.add_argument('--model', '-m') 50 | parser.add_argument('--data', '-d') 51 | args = parser.parse_args() 52 | 53 | 54 | # infer the groupby variable 55 | s, d, m = bool(args.space), bool(args.data), bool(args.model) 56 | assert not (s and d and m) 57 | assert (s or d or m) 58 | assert not (s ^ d ^ m) 59 | groupby = ['space', 'data', 'model'][np.argmin([s, d, m])] 60 | 61 | 62 | # first we want to just filter noise 63 | skipping = False 64 | keepers = [] 65 | with open(args.input) as results: 66 | for line in results: 67 | line = line.strip() 68 | if not line: continue 69 | if any(i in line for i in ignore): continue 70 | 71 | if line == 'False Positive Issue:': 72 | skipping = True 73 | elif line.startswith('SPACE:'): 74 | skipping = False 75 | 76 | if not skipping: 77 | keepers.append(line) 78 | 79 | # now parse out the actual items 80 | trials = parse_items(keepers) 81 | 82 | # and filter them according to the arguments 83 | present = [] 84 | for t in trials: 85 | if args.space and args.space not in t['space']: continue 86 | if args.data and args.data not in t['data']: continue 87 | if args.model and args.model not in t['model']: continue 88 | present.append(t) 89 | 90 | if not present: 91 | raise ValueError("Got no items, fool!") 92 | 93 | df = pd.DataFrame(present) 94 | df = df.groupby(groupby).aggregate({'mean': [np.min, np.mean, np.max]}) 95 | print df 96 | 97 | 98 | if __name__ == '__main__': 99 | main() 100 | -------------------------------------------------------------------------------- /scripts/filterspace.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import sys 3 | import argparse 4 | from space import load_mikolov_text 5 | 6 | def main(): 7 | parser = argparse.ArgumentParser('Reduces a vector space to only the limited vocab.') 8 | parser.add_argument('--input', '-i', help='Input space') 9 | parser.add_argument('--output', '-o', help='Output space') 10 | parser.add_argument('--whitelist', '-w', help='Whitelist file.') 11 | parser.add_argument('--dims', '-d', type=int, help='Number of dimensions') 12 | args = parser.parse_args() 13 | 14 | 15 | space = load_mikolov_text(args.input) 16 | 17 | if args.whitelist: 18 | whitelist = [] 19 | with open(args.whitelist) as wlf: 20 | for line in wlf: 21 | whitelist.append(line.strip().lower()) 22 | whitelist = set(whitelist) 23 | filtered = space.subset(whitelist) 24 | else: 25 | filtered = space 26 | if args.dims: 27 | filtered.matrix = filtered.matrix[:,:args.dims] 28 | filtered.save_mikolov_text(args.output) 29 | 30 | if __name__ == '__main__': 31 | main() 32 | 33 | -------------------------------------------------------------------------------- /scripts/generategraphs.R: -------------------------------------------------------------------------------- 1 | require(ggplot2) 2 | 3 | me <- read.csv("~/working/lexent/matcherror.csv") 4 | 5 | ggplot(me[me$features == "diff",], aes(x=recall, y=match_error, color=data, shape=features)) + geom_point(size=1.5) + geom_abline(intercept=0, slope=1) + xlim(0, 1) + ylim(0, 1) + theme_bw() # + scale_color_grey(start = 0.7, end=0.0) 6 | ggplot(me[me$features == "diffsq",], aes(x=recall, y=match_error, color=data, shape=features)) + geom_point(size=1.5) + geom_abline(intercept=0, slope=1) + xlim(0, 1) + ylim(0, 1) + theme_bw() # + scale_color_grey(start = 0.7, end=0.0) 7 | -------------------------------------------------------------------------------- /scripts/sigtest.py: -------------------------------------------------------------------------------- 1 | """ 2 | file mcnemar.py 3 | author Dr. Ernesto P. Adorio 4 | UPEPP at Clark Field, Pampanga 5 | desc Performs a nonparametric McNemar test for differences in two proportions. 6 | """ 7 | 8 | 9 | import sys 10 | import pandas as pd 11 | import numpy as np 12 | from math import sqrt 13 | from scipy import stats 14 | 15 | def mcnemar(A,B, C,D, alpha= 0.05, onetailed = False,verbose= False): 16 | """ 17 | Performs a mcnemar test. 18 | A,B,C,D- counts in the form 19 | A B A+B 20 | C D C+D 21 | A+C B+D n 22 | 23 | alpha - level of significance 24 | onetailed -False for two-tailed test 25 | True for one-tailed test 26 | Returns True if Null hypotheses pi1 == pi2 is accepted 27 | else False. 28 | """ 29 | tot = float(A + B + C + D) 30 | Z = (B-C)/ sqrt(B+C) 31 | 32 | if verbose: 33 | print "McNemar Test with A,B,C,D = ", A,B, C,D 34 | print "Ratios:p1, p2 = ",(A+B)/tot, (C + D) /tot 35 | print "Z test statistic Z = ", Z 36 | 37 | 38 | if onetailed: 39 | if (B-C> 0): 40 | zcrit2 = stats.norm.ppf(1-alpha) 41 | result = True if (Z < zcrit2)else False 42 | if verbose: 43 | print "Upper critical value=", zcrit2 44 | print "Decision:", "Accept " if (result) else "Reject ", 45 | print "Null hypothesis at alpha = ", alpha 46 | else: 47 | zcrit1 = stats.norm.ppf(alpha) 48 | result = False if (Z < zcrit1) else False 49 | if verbose: 50 | print "Lower critical value=", zcrit1 51 | print "Decision:", "Accept " if (result) else "Reject ", 52 | print "Null hypothesis at alpha = ", alpha 53 | 54 | 55 | else: 56 | zcrit1 = stats.norm.ppf(alpha/2.0) 57 | zcrit2 = stats.norm.ppf(1-alpha/2.0) 58 | 59 | result = True if (zcrit1 < Z < zcrit2) else False 60 | if verbose: 61 | print "Lower and upper critical limits:", zcrit1, zcrit2 62 | print "Decision:","Accept " if result else "Reject ", 63 | print "Null hypothesis at alpha = ", alpha 64 | 65 | return result 66 | 67 | if __name__ == '__main__': 68 | if len(sys.argv) != 3: 69 | print 'Usage: sigtest.py [output1file] [output2file]' 70 | table1 = pd.read_csv(sys.argv[1]) 71 | table2 = pd.read_csv(sys.argv[2]) 72 | 73 | assert len(table1) == len(table2) 74 | table1['correct'] = table1['prediction'] == table1['entails'] 75 | table2['correct'] = table2['prediction'] == table2['entails'] 76 | 77 | together = pd.merge(table1, table2, on=('word1', 'word2')) 78 | 79 | both_right = np.sum((together.correct_x == True) & (together.correct_y == True)) 80 | both_wrong = np.sum((together.correct_x == False) & (together.correct_y == False)) 81 | second_right = np.sum((together.correct_x == False) & (together.correct_y == True)) 82 | first_right = np.sum((together.correct_x == True) & (together.correct_y == False)) 83 | 84 | mcnemar(both_right, first_right, second_right, both_wrong, 0.05, False, True) 85 | 86 | -------------------------------------------------------------------------------- /scripts/svdspace.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | import sys 3 | import argparse 4 | import numpy as np 5 | from scipy.linalg import svd 6 | 7 | from space import load_mikolov_text, VectorSpace 8 | 9 | def main(): 10 | parser = argparse.ArgumentParser('Transforms the space by applying the SVD') 11 | parser.add_argument('--input', '-i', help='Input file') 12 | parser.add_argument('--output', '-o', help='Output file') 13 | args = parser.parse_args() 14 | 15 | space = load_mikolov_text(args.input) 16 | U, s, Vh = svd(space.matrix, full_matrices=False) 17 | transformed = U.dot(np.diag(s)) 18 | 19 | newspace = VectorSpace(transformed, space.vocab) 20 | newspace.save_mikolov_text(args.output) 21 | 22 | 23 | if __name__ == '__main__': 24 | main() 25 | --------------------------------------------------------------------------------