├── .DS_Store ├── README.md ├── inputdata.py ├── model.py ├── rw ├── README.txt └── rw.txt ├── word2vec2.py └── wordsim353 ├── combined.csv ├── combined.tab ├── instructions.txt ├── set1.csv ├── set1.tab ├── set2.csv └── set2.tab /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fanglanting/skip-gram-pytorch/0a16cd6b03f56ebca1854c4b07368ea826625d0f/.DS_Store -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | A complete pytorch implementation of skipgram model (with subsampling and negative sampling). 2 | The embedding result is tested with Spearman's rank correlation. 3 | -------------------------------------------------------------------------------- /inputdata.py: -------------------------------------------------------------------------------- 1 | import collections 2 | import numpy as np 3 | 4 | import math 5 | import os 6 | import random 7 | 8 | from six.moves import urllib 9 | from six.moves import xrange # pylint: disable=redefined-builtin 10 | data_index = 0 11 | class Options(object): 12 | def __init__(self, datafile, vocabulary_size): 13 | self.vocabulary_size = vocabulary_size 14 | self.save_path = "tmp" 15 | self.vocabulary = self.read_data(datafile) 16 | data_or, self.count, self.vocab_words = self.build_dataset(self.vocabulary, 17 | self.vocabulary_size) 18 | self.train_data = self.subsampling(data_or) 19 | #self.train_data = data_or 20 | 21 | self.sample_table = self.init_sample_table() 22 | 23 | self.save_vocab() 24 | 25 | def read_data(self,filename): 26 | with open(filename) as f: 27 | data = f.read().split() 28 | data = [x for x in data if x != 'eoood'] 29 | return data 30 | 31 | def build_dataset(self,words, n_words): 32 | """Process raw inputs into a .""" 33 | count = [['UNK', -1]] 34 | count.extend(collections.Counter(words).most_common(n_words - 1)) 35 | dictionary = dict() 36 | for word, _ in count: 37 | dictionary[word] = len(dictionary) 38 | data = list() 39 | unk_count = 0 40 | for word in words: 41 | if word in dictionary: 42 | index = dictionary[word] 43 | else: 44 | index = 0 # dictionary['UNK'] 45 | unk_count += 1 46 | data.append(index) 47 | count[0][1] = unk_count 48 | reversed_dictionary = dict(zip(dictionary.values(), dictionary.keys())) 49 | return data, count, reversed_dictionary 50 | 51 | def save_vocab(self): 52 | with open(os.path.join(self.save_path, "vocab.txt"), "w") as f: 53 | for i in xrange(len(self.count)): 54 | vocab_word = self.vocab_words[i] 55 | f.write("%s %d\n" % (vocab_word, self.count[i][1])) 56 | 57 | def init_sample_table(self): 58 | count = [ele[1] for ele in self.count] 59 | pow_frequency = np.array(count)**0.75 60 | power = sum(pow_frequency) 61 | ratio = pow_frequency/ power 62 | table_size = 1e8 63 | count = np.round(ratio*table_size) 64 | sample_table = [] 65 | for idx, x in enumerate(count): 66 | sample_table += [idx]*int(x) 67 | return np.array(sample_table) 68 | def weight_table(self): 69 | count = [ele[1] for ele in self.count] 70 | pow_frequency = np.array(count)**0.75 71 | power = sum(pow_frequency) 72 | ratio = pow_frequency/ power 73 | return np.array(ratio) 74 | def subsampling(self,data): 75 | count = [ele[1] for ele in self.count] 76 | frequency = np.array(count)/sum(count) 77 | P = dict() 78 | for idx, x in enumerate(frequency): 79 | y = (math.sqrt(x/0.001)+1)*0.001/x 80 | P[idx] = y 81 | subsampled_data = list() 82 | for word in data: 83 | if random.random()
len(data): 98 | data_index = 0 99 | buffer.extend(data[data_index:data_index + span]) 100 | data_index += span 101 | for i in range(batch_size): 102 | batch[i] = buffer[skip_window] 103 | targets = [x for x in range(skip_window)]+[x for x in range(skip_window+1,span)] 104 | for idj, j in enumerate(targets): 105 | labels[i,idj] = buffer[j] 106 | if data_index == len(data): 107 | buffer.extend(data[:span]) 108 | data_index = span 109 | self.process = False 110 | else: 111 | buffer.append(data[data_index]) 112 | data_index += 1 113 | # Backtrack a little bit to avoid skipping words in the end of a batch 114 | data_index = (data_index + len(data) - span) % len(data) 115 | return batch, labels 116 | 117 | def generate_batch(self, window_size, batch_size, count): 118 | data = self.train_data 119 | global data_index 120 | span = 2 * window_size + 1 121 | context = np.ndarray(shape=(batch_size,2 * window_size), dtype=np.int64) 122 | labels = np.ndarray(shape=(batch_size), dtype=np.int64) 123 | pos_pair = [] 124 | 125 | if data_index + span > len(data): 126 | data_index = 0 127 | self.process = False 128 | buffer = data[data_index:data_index + span] 129 | pos_u = [] 130 | pos_v = [] 131 | 132 | for i in range(batch_size): 133 | data_index += 1 134 | context[i,:] = buffer[:window_size]+buffer[window_size+1:] 135 | labels[i] = buffer[window_size] 136 | if data_index + span > len(data): 137 | buffer[:] = data[:span] 138 | data_index = 0 139 | self.process = False 140 | else: 141 | buffer = data[data_index:data_index + span] 142 | 143 | for j in range(span-1): 144 | pos_u.append(labels[i]) 145 | pos_v.append(context[i,j]) 146 | neg_v = np.random.choice(self.sample_table, size=(batch_size*2*window_size,count)) 147 | return np.array(pos_u), np.array(pos_v), neg_v 148 | 149 | 150 | 151 | 152 | import json, csv 153 | from scipy.stats import spearmanr 154 | import math 155 | def cosine_similarity(v1,v2): 156 | "compute cosine similarity of v1 to v2: (v1 dot v2)/{||v1||*||v2||)" 157 | sumxx, sumxy, sumyy = 0, 0, 0 158 | for i in range(len(v1)): 159 | x = v1[i]; y = v2[i] 160 | sumxx += x*x 161 | sumyy += y*y 162 | sumxy += x*y 163 | return sumxy/math.sqrt(sumxx*sumyy) 164 | 165 | def scorefunction(embed): 166 | f = open('./tmp/vocab.txt') 167 | line = f.readline() 168 | vocab = [] 169 | wordindex = dict() 170 | index = 0 171 | while line: 172 | word = line.strip().split()[0] 173 | wordindex[word] = index 174 | index = index +1 175 | line = f.readline() 176 | f.close() 177 | ze = [] 178 | with open('./wordsim353/combined.csv') as csvfile: 179 | filein = csv.reader(csvfile) 180 | index = 0 181 | consim = [] 182 | humansim = [] 183 | for eles in filein: 184 | if index==0: 185 | index = 1 186 | continue 187 | if (eles[0] not in wordindex) or (eles[1] not in wordindex): 188 | continue 189 | 190 | word1 = int(wordindex[eles[0]]) 191 | word2 = int(wordindex[eles[1]]) 192 | humansim.append(float(eles[2])) 193 | 194 | 195 | value1 = embed[word1] 196 | value2 = embed[word2] 197 | index =index + 1 198 | score = cosine_similarity(value1, value2) 199 | consim.append(score) 200 | 201 | 202 | cor1, pvalue1 = spearmanr(humansim, consim) 203 | 204 | if 1==1: 205 | lines = open('./rw/rw.txt','r').readlines() 206 | index = 0 207 | consim = [] 208 | humansim = [] 209 | for line in lines: 210 | eles = line.strip().split() 211 | if (eles[0] not in wordindex) or (eles[1] not in wordindex): 212 | continue 213 | word1 = int(wordindex[eles[0]]) 214 | word2 = int(wordindex[eles[1]]) 215 | humansim.append(float(eles[2])) 216 | 217 | value1 = embed[word1] 218 | value2 = embed[word2] 219 | index =index + 1 220 | score = cosine_similarity(value1, value2) 221 | consim.append(score) 222 | 223 | 224 | cor2, pvalue2 = spearmanr(humansim, consim) 225 | 226 | 227 | return cor1,cor2 228 | -------------------------------------------------------------------------------- /model.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from torch.autograd import Variable 3 | import torch.nn as nn 4 | import torch.nn.functional as F 5 | import numpy as np 6 | from inputdata import Options, scorefunction 7 | 8 | class skipgram(nn.Module): 9 | def __init__(self, vocab_size, embedding_dim): 10 | super(skipgram, self).__init__() 11 | self.u_embeddings = nn.Embedding(vocab_size, embedding_dim, sparse=True) 12 | self.v_embeddings = nn.Embedding(vocab_size, embedding_dim, sparse=True) 13 | self.embedding_dim = embedding_dim 14 | self.init_emb() 15 | def init_emb(self): 16 | initrange = 0.5 / self.embedding_dim 17 | self.u_embeddings.weight.data.uniform_(-initrange, initrange) 18 | self.v_embeddings.weight.data.uniform_(-0, 0) 19 | def forward(self, u_pos, v_pos, v_neg, batch_size): 20 | 21 | embed_u = self.u_embeddings(u_pos) 22 | embed_v = self.v_embeddings(v_pos) 23 | 24 | score = torch.mul(embed_u, embed_v) 25 | score = torch.sum(score, dim=1) 26 | log_target = F.logsigmoid(score).squeeze() 27 | 28 | neg_embed_v = self.v_embeddings(v_neg) 29 | 30 | neg_score = torch.bmm(neg_embed_v, embed_u.unsqueeze(2)).squeeze() 31 | neg_score = torch.sum(neg_score, dim=1) 32 | sum_log_sampled = F.logsigmoid(-1*neg_score).squeeze() 33 | 34 | loss = log_target + sum_log_sampled 35 | 36 | return -1*loss.sum()/batch_size 37 | def input_embeddings(self): 38 | return self.u_embeddings.weight.data.cpu().numpy() 39 | def save_embedding(self, file_name, id2word): 40 | embeds = self.u_embeddings.weight.data 41 | fo = open(file_name, 'w') 42 | for idx in range(len(embeds)): 43 | word = id2word(idx) 44 | embed = ' '.join(embeds[idx]) 45 | fo.write(word+' '+embed+'\n') 46 | -------------------------------------------------------------------------------- /rw/README.txt: -------------------------------------------------------------------------------- 1 | ########################################################################################## 2 | # Stanford Rare Word (RW) Similarity Dataset 3 | # Minh-Thang Luong, Richard Socher, and Christopher D. Manning. 4 | # Computer Science Department 5 | # Stanford University 6 | ########################################################################################## 7 | 8 | 9 | This dataset is available for download at http://nlp.stanford.edu/~lmthang/morphoNLM. It was collected and described in the following paper: 10 | @inproceedings{Luong-etal:conll13:morpho, 11 | Address = {Sofia, Bulgaria} 12 | Author = {Luong, Minh-Thang and Socher, Richard and Manning, Christopher D.}, 13 | Booktitle = {CoNLL}, 14 | Title = {Better Word Representations with Recursive Neural Networks for Morphology} 15 | Year = {2013}} 16 | 17 | ========================================================================== 18 | The dataset (rw.txt) consists of 2034 pairs, one per line. Each line consists of a pair of words, the average similarity rating and up to 10 individual ratings. Tokens are tab-delimited. 19 | 20 | --------------------------------------------------------------------------- 21 | Last modified: Aug 06, 2013 22 | -------------------------------------------------------------------------------- /rw/rw.txt: -------------------------------------------------------------------------------- 1 | squishing squirt 5.88 7 7 6 1 4 6 6 7 2 4 2 | undated undatable 5.83 10 9 6 5 5 7 7 9 2 5 3 | circumvents beat 5.33 7 7 3 9 8 6 3 2 0 6 4 | circumvents ebb 3.25 7 4 6 4 2 0 0 3 6 0 5 | dispossess deprive 6.83 10 6 7 10 10 8 5 8 1 7 6 | provincialism narrow-mindedness 8.11 9 7 9 9 8 6 9 7 0 9 7 | provincialism partiality 4.50 9 3 0 4 8 9 6 5 0 0 8 | instrumentality department 3.00 6 2 4 3 7 3 3 0 0 0 9 | instrumentality utility 7.29 6 7 7 5 8 7 9 8 3 8 10 | involvement action 6.86 7 8 7 8 5 9 6 9 7 1 11 | involvement implication 4.17 5 8 2 3 10 8 4 4 4 5 12 | ecclesiastic clergyman 8.67 10 8 10 10 8 6 8 0 9 9 13 | brigadier general 8.17 8 8 10 8 9 7 9 6 5 10 14 | carbonic chemical 5.17 7 3 5 4 8 7 9 0 2 5 15 | carbonic paper 5.17 8 7 6 2 8 7 7 0 0 2 16 | aspirate pronounce 5.20 8 4 2 10 7 6 0 0 7 0 17 | aspirate remove 2.50 6 3 7 3 2 0 2 0 18 | monotype machine 5.25 1 8 1 6 1 5 5 9 0 5 19 | incommensurate incommensurable 7.60 10 10 8 7 9 8 4 6 20 | campfires fire 9.33 10 9 9 9 9 10 10 8 10 6 21 | cognizance knowing 9.44 10 9 10 8 10 10 8 10 10 7 22 | urbanize change 5.67 4 2 2 7 5 7 4 10 2 7 23 | imperfection state 0.29 0 1 0 0 1 0 6 4 0 24 | assessment charge 4.40 0 8 2 1 7 8 5 7 0 25 | assessment assay 5.83 8 10 5 6 4 5 7 3 26 | incubate breed 6.40 10 6 10 5 7 4 7 7 27 | incubate develop 7.20 7 7 8 6 7 7 9 10 28 | principality domain 7.62 7 8 8 4 8 0 7 8 7 8 29 | vicarious abnormal 0.12 3 0 0 0 5 0 0 0 0 1 30 | vicarious secondary 6.50 7 8 0 9 5 0 10 8 2 31 | ungraceful awkward 8.50 10 7 9 9 10 7 8 10 7 8 32 | unsighted color-blind 5.29 6 5 7 4 6 5 5 0 6 33 | socialise educate 6.12 6 7 1 7 5 7 6 4 7 0 34 | socialise swing 1.00 5 6 1 3 0 4 0 0 0 0 35 | diagonals line 7.57 8 6 8 8 8 7 4 8 5 5 36 | diagonals heterosexual 0.11 0 1 0 0 0 3 0 0 0 0 37 | naturalise adapt 7.75 7 8 9 9 7 8 0 6 0 8 38 | insubordinate rebellious 9.00 10 8 8 9 10 8 9 10 9 9 39 | insubordinate defiant 9.56 10 9 9 10 10 7 10 10 9 9 40 | subdividing subdivide 9.50 9 10 10 10 10 6 10 9 7 8 41 | subdividing separate 8.67 9 9 8 8 10 6 10 9 9 0 42 | antifeminism sexism 8.60 10 9 9 6 10 5 5 9 9 7 43 | circumcising cut 8.00 7 8 8 7 8 10 10 8 8 7 44 | circumcising remove 8.17 8 8 6 6 8 10 9 8 8 5 45 | excommunicate oust 8.20 8 10 7 10 9 10 10 8 8 8 46 | accomplished over 5.00 7 0 4 0 10 10 0 7 2 5 47 | attackers wrongdoer 7.50 7 8 5 7 7 9 7 8 8 8 48 | contravened disagree 7.38 6 9 9 6 8 7 7 10 2 7 49 | contravened transgress 7.00 8 6 9 6 8 10 7 2 4 7 50 | tenderize change 5.88 7 0 4 6 4 5 7 7 7 0 51 | blithering chatter 7.71 8 10 6 7 9 10 6 9 4 9 52 | resurfacing coat 8.44 7 8 9 9 10 10 7 10 0 6 53 | resurfacing surface 6.50 8 5 6 4 8 5 8 7 10 5 54 | friendships brotherhood 7.50 8 7 6 8 7 6 9 7 9 8 55 | soulfully emotional 7.60 7 9 3 9 5 8 7 8 5 8 56 | elector voter 7.83 10 7 5 10 10 7 8 9 9 7 57 | intentionality intended 8.40 8 8 7 10 7 8 9 9 7 10 58 | vulgarism profanity 9.62 10 9 10 10 9 8 9 10 10 7 59 | vulgarism inelegance 6.29 5 4 6 9 1 9 8 8 7 6 60 | preliterate illiterate 4.71 5 7 5 5 5 7 3 5 5 0 61 | preliterate noncivilized 4.43 4 7 0 4 5 6 2 5 5 0 62 | retrying hear 0.38 0 4 0 0 3 5 0 0 0 0 63 | wanderers program 0.29 0 4 0 0 2 4 0 0 5 0 64 | wanderers nomad 9.50 10 9 10 10 10 9 9 9 10 9 65 | marginalize interact 2.50 3 0 0 2 5 0 6 0 3 2 66 | hyperlink link 9.12 8 10 9 4 6 10 8 8 10 10 67 | inducted admit 7.17 5 7 3 6 8 10 10 8 0 9 68 | inducted install 6.00 8 7 0 4 7 10 4 6 0 6 69 | entrapping capture 8.00 8 8 3 10 7 8 8 8 9 8 70 | entrapping deceive 6.57 5 8 4 8 7 3 9 2 7 7 71 | alleviated comfort 6.00 6 6 5 4 8 6 6 6 8 8 72 | alleviated help 6.00 6 6 5 7 6 7 4 3 8 5 73 | radiators beginning 0.00 0 0 0 5 4 0 0 0 0 0 74 | radiators system 1.00 0 2 0 6 6 1 7 0 4 0 75 | postmodernism genre 2.80 0 6 1 3 7 3 7 2 0 5 76 | excavations site 5.29 3 0 1 6 7 9 5 5 6 5 77 | excavations removal 7.43 3 6 0 8 8 10 9 8 5 8 78 | comfortable cozy 8.83 9 9 5 10 8 9 7 9 9 10 79 | unfeathered unfledged 7.14 6 6 9 9 4 8 8 3 0 10 80 | unfeathered plucked 8.00 10 8 9 9 7 7 9 7 10 6 81 | assigned regiment 3.80 1 6 0 7 6 0 2 0 4 8 82 | assigned allow 3.50 1 5 0 7 9 0 5 0 3 7 83 | listeners eavesdropper 8.14 8 6 5 7 10 8 9 8 8 9 84 | unheralded unexpected 7.57 3 6 5 9 8 9 10 8 8 3 85 | inabilities insufficiency 7.38 6 8 1 8 8 3 8 6 8 7 86 | inabilities incomprehension 4.33 2 7 3 6 0 6 4 0 5 7 87 | monocultures culture 4.50 8 5 5 8 1 4 6 3 8 4 88 | tricolour flag 5.80 7 6 6 3 0 1 10 7 0 9 89 | omnipotence state 0.86 5 3 0 6 2 1 0 0 6 0 90 | mingles change 1.71 2 5 1 2 0 1 2 1 0 3 91 | calcify harden 8.12 10 8 3 9 6 9 8 9 7 9 92 | calcify change 4.83 5 7 0 5 4 5 5 0 8 5 93 | disinheritance discontinuance 5.67 4 6 0 8 6 4 0 0 7 7 94 | interwove braid 8.75 9 9 4 9 9 8 10 8 9 9 95 | cession relinquishment 6.67 6 7 8 8 1 6 2 5 10 0 96 | dwarfish small 8.38 9 7 3 10 9 9 9 7 9 8 97 | assessments charge 5.12 7 4 3 6 0 6 8 7 5 3 98 | assessments classification 6.86 4 8 1 6 8 10 9 7 0 6 99 | prescriptions medicine 9.11 10 5 9 9 9 10 8 9 9 9 100 | prescriptions direction 2.57 5 1 7 5 1 0 6 1 4 1 101 | antipsychotic lithium 8.17 10 8 10 8 8 7 7 8 9 8 102 | circumferential peripheral 7.33 7 7 7 8 0 5 8 9 6 9 103 | roosters cockerel 8.56 10 10 9 2 10 6 10 6 9 7 104 | nonpublic private 10.00 10 10 10 10 10 10 8 10 9 10 105 | yodeling sing 7.71 10 7 8 9 8 10 5 8 7 7 106 | yodeling singing 7.50 10 7 8 10 8 10 5 8 7 7 107 | autoerotic sexy 8.44 10 10 10 8 10 4 9 7 6 6 108 | unisons concurrence 7.56 7 9 8 7 0 8 9 8 6 6 109 | unisons agreement 7.14 7 10 8 7 7 9 9 7 7 7 110 | disassembled destroy 8.00 8 6 8 9 6 9 7 10 8 7 111 | preteens juvenile 8.40 10 8 10 8 9 10 7 9 8 7 112 | unaccessible pathless 7.25 6 6 10 9 0 9 7 9 5 7 113 | monogram symbol 7.25 4 10 9 9 6 7 9 7 7 0 114 | opalescence brightness 7.89 10 9 10 0 7 6 10 8 5 6 115 | estrogenic hormone 8.00 5 6 10 6 8 0 9 8 10 10 116 | misleading beat 1.25 0 3 0 0 4 0 3 6 7 0 117 | consubstantial considerable 5.40 7 0 7 0 4 7 0 2 8 118 | coeducation education 7.71 5 7 9 10 6 7 5 8 8 9 119 | canonical standard 6.00 9 9 8 4 0 6 5 7 1 6 120 | galvanic exciting 6.00 9 5 0 6 7 0 7 5 121 | nominated nominate 8.33 9 10 9 10 8 10 8 8 8 5 122 | nominated choose 8.67 7 10 10 10 7 10 8 9 7 3 123 | exceedance probability 5.00 7 7 0 6 5 0 6 6 2 0 124 | confide consign 5.14 6 6 0 6 4 0 5 5 10 4 125 | confide unwrap 0.67 1 0 0 0 2 1 0 2 5 0 126 | established initiate 5.86 0 5 8 3 7 5 6 10 7 0 127 | condescend act 2.20 3 3 2 1 0 2 4 0 4 0 128 | tricycle pedicab 6.00 8 7 9 0 4 9 5 6 7 5 129 | discharged spread 4.57 0 3 6 2 6 5 6 7 4 0 130 | postmodernist artist 6.57 8 7 7 3 9 10 5 6 7 6 131 | ruralist rustic 7.86 8 8 5 7 9 10 5 7 7 9 132 | ruralist advocate 0.67 0 2 2 2 4 0 0 0 0 0 133 | conjurors enchantress 7.50 9 9 7 5 6 9 9 6 3 134 | detestable offensive 8.75 10 9 6 9 5 10 8 9 10 6 135 | detestable hateful 9.62 10 9 7 9 8 10 10 9 10 10 136 | comparing compare 10.00 8 10 10 10 10 10 10 10 10 7 137 | comparing analogize 8.00 8 5 8 7 7 8 10 9 5 9 138 | marketers selling 8.43 9 10 7 4 9 9 8 10 9 8 139 | hypercoaster roller 3.25 0 7 4 0 4 9 0 8 2 3 140 | pittance payment 5.14 2 5 5 5 5 8 8 6 6 4 141 | soulless insensitive 7.17 6 7 8 5 9 8 9 7 7 5 142 | hypermarket supermarket 5.00 2 5 9 9 4 10 6 5 0 143 | confluent branch 4.20 2 3 8 7 6 5 0 5 0 144 | confluent convergent 6.29 4 6 7 8 8 0 8 3 145 | anterooms building 6.14 4 6 7 7 6 7 9 6 1 10 146 | reasoning deduce 8.00 7 8 9 10 8 9 8 10 7 6 147 | reasoning re-argue 4.00 1 6 2 3 5 7 7 4 0 4 148 | summonings page 5.43 6 5 9 5 4 7 7 0 8 4 149 | summonings demand 7.14 5 5 9 10 7 9 7 0 8 1 150 | preordained predetermine 8.50 7 8 9 10 8 9 9 10 8 7 151 | antechamber room 7.88 7 7 9 8 8 9 10 8 7 3 152 | concavity shape 6.67 5 6 9 7 7 6 9 7 7 4 153 | concavity recess 7.67 6 6 8 6 9 7 9 10 8 6 154 | unzipping unfasten 8.29 8 9 6 8 9 8 9 10 7 6 155 | spoonful containerful 4.20 4 8 3 2 7 7 5 4 0 5 156 | partible divisible 7.71 10 6 7 7 8 9 8 10 8 7 157 | hypersensitive susceptible 6.33 0 5 7 3 8 10 7 8 158 | impurity adulteration 6.33 10 6 4 5 8 8 6 5 159 | impurity waste 4.83 5 4 7 0 8 0 5 3 9 5 160 | inscribe engrave 8.67 10 7 9 8 9 10 10 8 9 9 161 | virginals harpsichord 1.86 1 3 0 8 0 4 5 0 162 | hypertexts database 7.00 5 8 0 8 0 1 7 9 7 7 163 | inheritances acquisition 6.83 10 5 7 1 8 9 3 9 0 164 | infectious septic 7.00 10 8 7 2 8 10 10 6 6 0 165 | infectious contagious 9.25 10 8 9 10 9 5 10 8 6 10 166 | pinpointed locate 9.22 9 9 8 7 9 10 10 8 10 10 167 | capitalised profit 7.60 5 7 9 2 9 10 10 8 2 0 168 | capitalised supply 5.17 5 7 7 0 8 0 5 6 1 0 169 | retrace return 7.25 8 8 8 2 8 0 8 8 5 5 170 | deadness quality 0.38 0 0 3 0 0 4 0 1 2 0 171 | deadness inelasticity 4.29 3 0 5 8 6 0 6 5 2 3 172 | conformism legalism 3.67 9 5 7 6 0 4 0 2 2 3 173 | tripods tripod 10.00 10 9 9 10 10 10 9 10 10 10 174 | lastingly wear 3.00 8 0 2 1 3 0 5 7 4 3 175 | lastingly populate 0.43 1 0 4 0 0 0 6 0 4 2 176 | unexpected unannounced 8.00 6 9 8 10 8 5 8 7 10 8 177 | interlink intercommunicate 7.00 10 5 7 7 7 0 8 9 5 8 178 | interlink connect 9.22 10 7 10 10 10 9 9 8 8 9 179 | brained kill 1.75 0 0 7 5 10 0 4 0 3 2 180 | brained hit 3.40 0 0 10 5 10 2 4 0 4 2 181 | unicycles wheel 6.88 10 5 7 8 8 0 7 5 8 7 182 | unicycles bicycle 6.57 9 5 8 7 8 0 7 5 6 9 183 | preservers cook 5.17 6 0 6 6 7 0 5 0 5 3 184 | preservers worker 2.80 6 1 3 3 6 0 5 0 7 2 185 | autografts graft 5.33 2 7 0 0 7 6 8 6 8 4 186 | retarding decelerate 7.88 6 8 0 8 8 9 9 2 7 8 187 | retarding stay 4.20 4 5 0 2 0 7 7 4 1 6 188 | subfamily group 8.00 7 10 7 5 10 9 6 8 8 9 189 | encrust coat 8.44 8 10 0 8 9 10 8 8 9 6 190 | encrust decorate 6.71 6 8 0 9 7 7 7 4 8 3 191 | wingless flightless 8.80 9 10 7 6 7 10 9 9 9 8 192 | intraspecific interspecies 5.50 8 4 0 0 0 7 6 8 5 193 | tunneled penetrate 6.33 7 9 1 5 5 9 7 1 7 7 194 | tunneled dig 8.71 9 10 9 7 9 10 8 8 9 9 195 | suppressor gene 3.75 7 0 0 2 0 4 3 6 8 8 196 | suppressor restrainer 9.22 8 10 7 9 10 10 10 8 9 9 197 | expound elaborate 8.67 9 10 8 9 10 8 7 9 9 10 198 | expound detail 8.88 9 9 8 9 8 0 3 9 9 10 199 | brisker energetic 8.33 7 9 8 9 9 8 8 2 8 9 200 | brisker invigorating 8.62 8 9 8 7 6 9 9 8 9 9 201 | wealthy rich 9.67 8 10 10 9 10 9 10 9 10 10 202 | eventful important 7.86 9 9 9 8 5 3 7 8 10 0 203 | eventful lively 7.57 7 8 8 8 3 7 9 7 8 2 204 | edgeless dull 7.43 8 8 7 6 10 1 7 9 7 10 205 | clownish humorous 7.67 9 9 7 5 7 8 9 8 8 8 206 | inquisitor thousand 0.29 2 0 1 1 0 0 0 2 3 0 207 | inquisitor inquirer 7.80 7 10 7 5 5 9 9 7 10 10 208 | extravert extroversive 7.83 7 10 7 8 5 9 7 9 10 209 | finality conclusive 8.57 8 10 7 6 8 9 9 9 9 8 210 | gibberish dutch 4.00 6 9 6 1 0 0 0 3 8 211 | championship status 4.60 5 1 5 4 3 0 8 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defensive 4.75 6 9 1 0 5 0 0 8 7 1768 | displeases repel 7.00 7 8 3 7 6 7 2 6 7 8 1769 | reproachful unfavorable 6.00 6 6 1 8 5 8 2 7 0 8 1770 | independently worker 2.80 1 2 0 5 6 1 0 5 0 7 1771 | independently individualist 8.12 7 9 0 10 8 10 0 8 8 5 1772 | extrajudicial illegal 5.40 4 4 1 10 2 8 10 8 3 1773 | exterminated destroy 9.33 9 10 3 10 9 10 10 8 9 9 1774 | exterminated kill 9.78 10 10 4 10 9 10 10 10 10 9 1775 | intercede negociate 6.86 7 8 2 6 6 9 2 8 6 7 1776 | postdates follow 5.60 6 9 0 6 5 0 4 9 0 7 1777 | postdates chronologize 6.71 7 5 0 10 7 8 2 8 6 6 1778 | comport about 0.00 0 0 0 6 6 0 0 0 5 1779 | comport misbehave 1.62 5 0 10 2 0 5 0 1 0 1780 | stockers animal 0.00 0 0 0 0 4 0 0 0 0 6 1781 | ceremonious formal 8.33 10 6 10 8 8 9 10 8 8 9 1782 | authorship initiation 6.20 6 7 0 7 0 7 4 0 1783 | slacken decrease 7.60 10 4 10 10 8 4 8 7 6 9 1784 | slacken weaken 6.33 0 4 10 10 7 10 8 6 4 9 1785 | freshen regenerate 8.44 10 2 10 6 8 10 9 8 6 9 1786 | freshen wash 7.14 5 7 8 7 8 10 10 8 7 1 1787 | observed comment 5.71 0 6 7 6 6 9 5 3 1 7 1788 | observed discover 6.83 10 5 9 7 7 10 6 4 4 7 1789 | hydrolysed change 5.43 4 0 7 7 7 8 6 4 3 8 1790 | enjoins instruct 5.00 4 3 7 0 6 9 5 2 9 1791 | replacements stand-in 9.25 10 9 10 10 7 10 8 8 9 1792 | replacements supplanting 6.00 2 5 6 8 10 10 5 6 10 1793 | bengali ethnic 6.38 6 2 8 10 5 7 6 5 7 7 1794 | transsexual person 8.00 8 3 3 5 9 9 1 9 10 8 1795 | automates change 2.00 6 1 0 8 0 0 5 8 0 4 1796 | amateurish unprofessional 8.50 10 7 8 9 8 10 9 9 10 8 1797 | sponsorship support 8.20 10 9 6 10 10 10 8 8 8 8 1798 | ejector person 0.75 4 0 0 7 1 0 6 1 0 0 1799 | ejector mechanism 7.62 6 0 8 9 9 0 8 7 8 6 1800 | rehashing recycle 8.33 9 6 9 9 4 8 5 9 10 10 1801 | preassembled produce 5.50 4 0 5 9 9 0 5 6 7 6 1802 | fascinate matter 1.71 0 0 7 6 0 6 0 7 0 7 1803 | fascinate interest 8.29 5 9 9 10 8 8 8 10 8 8 1804 | riskless safe 9.44 10 9 9 10 10 9 10 8 4 10 1805 | incombustible fireproof 9.00 8 9 9 10 9 10 10 9 9 10 1806 | rareness scarcity 9.00 9 9 9 10 10 9 9 8 10 10 1807 | lengthy long 10.00 10 10 10 10 10 9 10 10 10 1808 | lordship authority 8.00 9 7 9 9 6 7 9 9 7 2 1809 | lordship title 7.38 9 6 7 10 8 7 9 5 8 1 1810 | grinder sandwich 9.33 10 9 10 0 0 8 10 9 0 1811 | grinder wisdom 0.00 0 0 0 0 0 0 0 9 0 1812 | algebraic quadratics 7.25 8 9 7 8 0 8 4 8 6 1813 | congeniality friendliness 9.50 7 10 10 10 5 9 10 8 10 9 1814 | congeniality compatibility 6.29 9 7 8 9 5 8 5 6 5 4 1815 | portioned distribute 5.80 4 6 9 10 5 6 6 6 10 1816 | piquancy spiciness 9.25 10 9 9 10 7 8 8 10 10 1817 | piquancy quality 3.33 5 0 6 0 2 3 6 0 1818 | commenting note 9.00 8 8 9 10 8 8 9 9 9 9 1819 | commenting explain 7.86 9 7 10 7 6 7 9 10 8 8 1820 | reprocessing reclaim 5.33 2 6 0 7 5 6 6 8 8 0 1821 | roosted settle 7.67 10 7 3 7 8 3 7 8 9 0 1822 | roosted sit 6.86 8 6 6 6 9 10 5 7 8 7 1823 | immobilizing beat 1.50 0 3 0 5 4 0 8 6 0 0 1824 | immobilizing withhold 3.80 5 4 1 1 5 0 3 6 8 2 1825 | promised declare 6.20 2 5 0 5 9 9 9 6 7 8 1826 | employments state 3.75 0 4 0 2 0 6 6 0 4 5 1827 | employments populace 3.33 2 4 0 5 0 6 0 4 1828 | transposable exchangeable 7.17 10 8 6 10 7 9 2 6 7 10 1829 | protractors drafting 5.83 1 8 0 5 9 7 4 6 10 5 1830 | religiousness piety 7.50 10 6 7 9 7 10 8 1 0 8 1831 | religiousness conscientiousness 4.00 8 2 6 3 5 3 5 0 9 1832 | concerts settle 0.44 0 2 0 0 0 2 5 0 0 0 1833 | concerts plan 0.50 0 4 0 0 0 7 5 0 0 0 1834 | postholes hole 5.50 1 0 8 5 7 5 0 9 5 1835 | liveable habitable 10.00 10 9 9 10 9 10 10 9 10 10 1836 | besieging attack 8.22 7 6 1 6 10 10 8 8 9 10 1837 | besieging distress 5.50 6 0 1 5 0 7 6 3 6 10 1838 | irregardless look 0.00 4 0 0 0 4 0 0 0 0 1839 | irregardless prize 0.00 3 0 0 0 0 2 0 0 0 0 1840 | attendance frequency 4.83 5 3 6 0 7 1 5 6 1 4 1841 | attendance presence 8.25 8 7 7 7 10 10 8 9 10 8 1842 | computer expert 0.71 5 0 1 0 0 0 6 5 2 2 1843 | computer server 6.67 7 6 3 1 6 10 7 6 9 8 1844 | subtend shepherd 5.33 0 5 0 6 8 6 6 5 4 0 1845 | subtend suffer 0.38 0 0 2 0 1 5 0 0 4 0 1846 | irrelevance inapplicability 8.33 9 10 7 8 8 9 8 7 0 9 1847 | desiccating dry 8.56 6 9 0 6 9 10 9 9 10 9 1848 | desiccating preserve 5.86 6 1 5 6 9 8 6 10 4 6 1849 | transforming transubstantiate 7.17 7 10 0 6 0 8 6 10 7 9 1850 | transforming change 8.50 9 8 8 7 10 10 9 7 10 10 1851 | prisoners internee 6.17 9 4 6 10 10 10 1 5 8 5 1852 | cosponsors sponsor 8.67 7 9 8 10 10 9 9 8 8 3 1853 | unconvincing implausible 7.00 8 9 9 7 9 7 7 6 3 7 1854 | unconvincing unpersuasive 10.00 10 10 9 10 10 10 10 10 10 8 1855 | analogous similar 8.17 8 5 7 8 10 9 10 8 10 9 1856 | preheating heat 7.12 6 8 7 9 7 8 7 7 7 2 1857 | irrigate hush 0.50 1 0 4 0 0 0 1 2 6 0 1858 | irrigate treat 4.00 5 5 5 0 0 3 0 9 5 1 1859 | immortalize remind 4.33 5 5 4 6 4 6 5 3 1 0 1860 | immortalize change 2.33 1 3 6 4 3 2 6 1 0 0 1861 | unploughed untilled 8.60 9 10 9 10 10 8 9 8 6 7 1862 | syntaxes system 6.12 3 2 7 7 0 7 7 7 5 6 1863 | syntaxes structure 7.38 8 7 7 9 7 8 8 7 7 6 1864 | enforcing execute 7.86 9 8 6 6 8 10 9 5 9 3 1865 | enforcing compel 7.25 6 7 9 6 9 10 8 7 1 6 1866 | devilish playful 6.38 7 0 7 7 7 3 7 6 7 0 1867 | devilish evil 8.89 9 8 7 2 10 9 10 10 10 7 1868 | ganging group 7.67 6 8 6 7 9 8 10 6 9 6 1869 | dissimulate disguise 7.25 9 2 3 9 8 9 8 6 0 6 1870 | enhancement improvement 9.75 10 8 9 8 10 10 10 10 10 9 1871 | reconstructs construct 7.14 6 8 7 8 3 8 8 2 9 5 1872 | entrench fasten 4.20 0 3 5 8 6 0 8 2 5 0 1873 | entrench trespass 1.75 0 1 0 3 0 2 0 2 2 3 1874 | spherical round 9.00 9 10 8 7 9 0 10 9 9 10 1875 | impolitic inexpedient 5.14 6 5 6 8 6 0 1 6 3 4 1876 | londoners person 5.17 6 6 3 2 5 5 8 4 5 7 1877 | predetermination decision 6.17 2 9 6 6 5 8 10 2 6 6 1878 | destabilization change 6.14 6 5 8 9 5 6 10 3 8 5 1879 | reasonable moderate 7.67 7 8 8 5 10 7 10 6 8 8 1880 | reasonable rational 8.33 0 8 10 8 9 6 10 7 8 9 1881 | pottery lusterware 7.57 7 8 8 9 8 5 6 8 8 3 1882 | pottery trade 2.50 5 1 1 2 6 1 0 7 5 0 1883 | unenthusiastic halfhearted 8.50 10 7 7 7 10 9 10 8 7 10 1884 | virility masculinity 7.00 7 8 7 6 8 10 6 5 10 10 1885 | virility maleness 7.00 7 7 5 8 4 10 7 6 10 10 1886 | discordance dissonance 7.67 8 9 5 8 7 8 7 8 9 9 1887 | discordance strife 7.86 9 7 8 6 9 10 7 7 10 8 1888 | plundered destroy 8.71 10 5 9 9 9 8 9 9 8 10 1889 | plundered steal 9.75 8 9 10 8 10 9 10 10 10 10 1890 | transvestite person 4.86 7 5 3 5 10 1 6 5 8 3 1891 | transvestite homosexual 3.67 9 10 4 4 2 3 5 4 9 0 1892 | retraction motion 5.83 6 6 6 8 8 6 5 4 4 6 1893 | retraction withdrawal 8.75 10 9 5 10 9 10 8 9 3 2 1894 | enslaves subjugate 8.78 9 8 8 10 9 10 8 7 3 10 1895 | carburettors mechanical 7.57 10 7 6 8 2 9 7 9 3 7 1896 | explorer diver 6.86 9 6 6 7 7 2 8 6 8 2 1897 | perfectible perfect 6.67 7 7 2 9 8 9 5 6 9 7 1898 | stimulates prompt 4.50 8 6 6 10 6 2 0 3 4 0 1899 | stimulates quicken 6.43 6 7 7 10 6 0 0 7 5 7 1900 | concurrencies agreement 9.11 8 8 9 8 10 9 10 5 10 10 1901 | concurrencies cooperation 6.83 5 7 2 8 9 8 7 2 6 10 1902 | emulsify change 5.00 1 10 7 5 5 2 3 7 3 1903 | internationalisms scope 0.43 5 5 0 4 0 0 0 3 0 0 1904 | internationalisms doctrine 3.80 6 5 1 4 0 7 0 5 4 0 1905 | cylindric rounded 8.12 7 6 3 10 8 10 0 10 10 4 1906 | sexually sexy 8.00 7 8 5 10 8 9 8 5 8 8 1907 | afghani iranian 5.20 8 8 0 5 8 0 5 3 6 7 1908 | animalism doctrine 0.86 5 6 0 2 0 0 0 4 5 0 1909 | animalism disposition 3.25 3 6 0 4 0 0 2 4 1910 | latinist classicist 6.29 7 7 6 6 0 5 2 5 9 8 1911 | punjabi sanskrit 6.00 7 8 0 7 5 5 5 3 8 7 1912 | punjabi indian 6.83 8 9 3 9 8 6 6 6 9 7 1913 | exterminate destroy 9.67 10 9 10 8 10 10 9 10 9 10 1914 | exterminate kill 9.88 10 5 10 5 10 10 10 10 9 10 1915 | consign check 2.67 7 4 0 1 3 0 4 1 3 0 1916 | respectively individual 3.75 0 2 6 0 9 1 9 0 6 9 1917 | receiving fence 0.14 0 3 2 0 0 0 2 0 1 0 1918 | unicycle wheel 7.00 10 2 6 3 8 8 6 7 7 10 1919 | unicycle bicycle 7.29 8 8 7 7 8 6 3 7 10 1 1920 | incised cut 8.78 8 6 2 8 10 10 10 8 9 10 1921 | incised compound 1.14 5 4 0 2 2 0 5 0 0 1922 | perfective future 0.62 3 1 0 0 0 2 2 3 0 0 1923 | perfective aspect 3.40 1 0 6 8 0 0 3 4 3 10 1924 | apprenticeship position 5.75 6 0 7 8 5 5 6 4 6 7 1925 | reporters reporter 9.78 10 10 9 10 10 10 10 9 4 10 1926 | houseful containerful 4.71 4 0 5 5 5 0 5 4 7 5 1927 | irreverence evil 1.62 2 0 0 8 0 0 3 4 4 7 1928 | unostentatious tasteful 7.50 8 6 0 9 10 0 7 7 0 8 1929 | disadvantaged underprivileged 8.14 9 5 8 9 10 10 9 7 8 7 1930 | combatted wrestle 6.60 9 2 2 8 5 1 9 6 6 8 1931 | snooper eavesdropper 8.89 10 9 9 9 10 7 10 9 5 7 1932 | researchers fieldworker 6.50 7 3 7 8 5 1 7 3 6 7 1933 | resides populate 6.50 5 0 6 9 10 5 9 4 5 9 1934 | individualize distinguish 8.29 8 4 8 8 10 10 9 7 9 9 1935 | individualize change 4.25 3 0 0 8 5 0 8 6 8 3 1936 | coinsurance insurance 6.50 6 9 6 6 8 7 7 6 6 9 1937 | micrometer nanometer 7.14 10 6 8 8 7 6 3 8 7 4 1938 | micrometer caliper 2.83 7 4 7 1 5 2 1 2 2 2 1939 | postcode address 8.00 6 8 8 7 10 8 9 5 8 1940 | encrusted coat 7.29 8 9 8 4 8 7 10 6 7 7 1941 | encrusted decorate 5.83 6 8 8 6 5 7 3 6 5 2 1942 | undissolved unmelted 9.22 10 9 9 8 10 8 10 10 5 9 1943 | fastness fast 8.12 10 7 3 0 10 10 9 7 1 9 1944 | remainder sell 2.17 2 4 0 0 1 3 3 3 1 5 1945 | remainder part 6.17 10 8 5 1 7 4 7 9 1 6 1946 | marginality position 6.14 6 5 6 0 7 6 6 2 1 7 1947 | unmanned faze 1.62 0 2 0 9 6 2 1 3 0 5 1948 | refuels fuel 7.86 9 7 9 5 10 9 7 3 6 8 1949 | sidewinder rattlesnake 7.29 7 8 9 8 8 3 6 6 3 8 1950 | sidewinder missile 7.29 8 8 8 10 7 2 7 8 3 5 1951 | federalize unite 7.43 7 8 7 8 8 10 7 10 10 7 1952 | casteless unwanted 7.50 5 7 8 4 10 8 7 10 10 10 1953 | animalize change 3.00 0 5 1 3 6 6 8 0 3 0 1954 | reproves knock 5.50 6 8 4 8 0 7 8 0 5 0 1955 | characters being 4.40 2 2 1 3 9 8 7 9 10 0 1956 | characters scratch 0.00 0 0 0 0 0 0 1 0 0 1 1957 | conjecture hypothesis 10.00 10 10 10 9 10 9 9 9 10 10 1958 | symmetrical balanced 10.00 10 10 9 10 9 10 9 10 10 9 1959 | allurement temptation 9.78 9 10 6 9 10 10 10 10 10 10 1960 | allurement invitation 8.86 6 9 9 8 9 9 10 9 10 9 1961 | binging eat 7.43 9 2 5 6 9 10 3 7 7 9 1962 | extractor forceps 8.50 8 9 8 6 9 5 6 8 9 10 1963 | photographer paparazzo 7.60 7 5 10 5 8 10 7 8 10 8 1964 | perspectives eye 4.67 6 9 0 4 6 3 4 8 5 8 1965 | perspectives point 6.43 6 9 6 5 8 0 7 7 6 9 1966 | disinflation economic 5.83 9 5 3 5 6 3 7 8 6 6 1967 | interplanetary international 5.62 6 3 5 5 7 0 6 7 6 10 1968 | interplanetary unsettled 2.00 2 5 0 4 0 5 0 8 0 1969 | trilogies trio 8.33 8 9 7 7 10 10 10 8 10 7 1970 | poisoning corrupt 7.25 7 9 6 5 9 5 8 8 5 9 1971 | poisoning poison 9.62 9 10 9 10 10 7 10 9 10 6 1972 | bobbers float 9.00 9 9 9 8 10 9 9 8 10 10 1973 | portrayer painter 7.29 8 10 8 3 8 8 6 7 6 10 1974 | invariable hard-and-fast 6.57 5 8 7 8 3 0 7 0 8 10 1975 | invariable parameter 3.60 7 0 6 5 3 3 0 4 3 0 1976 | constrict astringe 6.33 0 10 7 6 0 6 10 10 0 1977 | constrict choke 8.40 9 6 10 7 10 10 6 8 9 9 1978 | extraversion sociability 8.71 10 9 8 5 8 9 9 9 10 9 1979 | frivolously superficial 7.86 9 3 0 5 9 9 7 8 10 8 1980 | remounted mount 7.60 6 8 8 8 6 9 7 9 7 5 1981 | remounted hop 0.29 7 0 0 0 6 0 0 2 8 0 1982 | reviles abuse 5.86 8 2 5 0 6 8 0 4 10 8 1983 | discounters mercantile 5.67 6 0 5 5 1 8 5 6 9 7 1984 | confinement restraint 9.33 9 5 10 10 10 9 8 9 10 9 1985 | consciousness knowing 8.20 8 8 7 10 10 8 7 9 7 8 1986 | consciousness self 5.86 5 10 5 0 10 5 8 5 6 7 1987 | believing feel 6.00 7 6 5 7 5 1 9 0 6 2 1988 | believing believe 9.75 9 8 10 10 10 10 10 10 9 8 1989 | regimental control 7.00 10 7 2 9 10 2 7 4 9 7 1990 | regimental form 5.00 9 5 0 7 0 3 7 5 8 3 1991 | subdivided subdivide 9.50 10 6 9 9 10 10 10 9 9 5 1992 | subdivided divide 6.00 9 7 5 0 10 8 7 5 5 5 1993 | sustainable continue 7.86 8 8 7 0 8 7 9 0 10 8 1994 | standardise gauge 6.50 8 7 3 6 5 1 5 8 9 10 1995 | standardise measure 7.12 9 6 8 7 8 9 5 0 10 5 1996 | defrayed pay 3.80 7 9 0 0 3 4 1 4 10 0 1997 | devilishly cook 0.22 5 2 0 0 0 0 0 0 0 0 1998 | devilishly antagonize 5.50 7 5 0 0 0 6 6 2 7 8 1999 | disapproving discountenance 5.40 9 3 7 0 8 3 2 6 9 10 2000 | subspaces mathematical 6.57 4 7 1 7 10 6 0 6 8 8 2001 | connoting imply 7.67 7 9 9 8 8 7 8 8 5 6 2002 | connoting express 5.57 7 2 8 7 4 8 4 7 5 5 2003 | inheritance transfer 5.71 6 0 7 9 7 6 2 0 7 5 2004 | inheritance acquisition 7.00 6 4 7 9 9 7 3 9 8 3 2005 | archery sport 7.00 8 6 3 9 9 8 6 7 9 7 2006 | sufficed serve 5.20 7 2 6 8 6 1 0 5 2007 | belligerence hostility 8.67 9 8 8 9 10 7 9 9 7 6 2008 | procreating brood 7.17 7 5 6 9 7 5 7 5 8 8 2009 | gelatinous thick 8.00 9 8 8 8 7 8 8 8 9 8 2010 | villainous wicked 9.75 10 10 9 10 10 9 8 10 10 2011 | harmony congruity 8.25 8 8 8 9 8 8 8 4 9 5 2012 | harmony music 7.25 7 9 5 8 9 7 9 6 9 7 2013 | inoffensive innocuous 8.83 9 10 9 9 8 6 9 6 9 10 2014 | insurrectionist young 3.00 5 3 1 5 4 2 5 0 2015 | inquisitive curious 8.40 8 8 9 9 7 10 10 8 10 10 2016 | inquisitive inquiring 8.43 8 9 8 9 8 6 7 10 9 8 2017 | extraterrestrial hypothetical 3.20 4 2 4 6 6 1 0 5 0 2018 | triclinic monoclinic 5.40 5 7 6 3 7 5 6 5 2019 | murderer killer 9.78 10 10 10 10 9 10 7 10 10 9 2020 | concurrency agreement 9.00 10 8 4 8 8 10 9 10 1 9 2021 | concurrency cooperation 7.33 9 6 6 7 6 9 6 8 0 9 2022 | historically real 4.71 4 6 3 2 5 5 4 6 7 0 2023 | nontoxic antitoxic 7.00 2 8 6 10 7 6 2 10 8 7 2024 | nontoxic edible 6.43 8 5 6 10 6 6 7 9 7 1 2025 | strengthened sandbag 5.00 7 1 6 5 7 0 0 3 6 7 2026 | strengthened brace 7.17 9 7 7 7 7 7 5 8 5 9 2027 | incontrovertible undeniable 7.50 10 7 7 3 8 10 10 8 9 6 2028 | incontrovertible incontestable 7.50 10 6 7 3 8 10 7 8 5 9 2029 | rumbled sound 6.50 1 7 9 1 5 7 6 7 7 0 2030 | intragroup intramural 6.38 7 7 4 6 10 6 7 6 0 8 2031 | exceptionally extraordinary 8.80 9 9 7 6 9 10 8 10 7 9 2032 | irredeemable wicked 6.43 5 4 7 6 7 10 6 6 3 8 2033 | irredeemable inconvertible 6.57 8 9 6 3 2 0 9 4 7 10 2034 | snickering laugh 7.71 8 8 7 5 7 9 8 8 8 9 2035 | -------------------------------------------------------------------------------- /word2vec2.py: -------------------------------------------------------------------------------- 1 | import zipfile 2 | import collections 3 | import numpy as np 4 | 5 | import math 6 | import random 7 | 8 | 9 | import torch 10 | import torch.nn as nn 11 | from torch.autograd import Variable 12 | import torch.optim as optim 13 | import torch.nn.functional as Func 14 | from torch.optim.lr_scheduler import StepLR 15 | import time 16 | 17 | from inputdata import Options, scorefunction 18 | from model import skipgram 19 | 20 | 21 | 22 | class word2vec: 23 | def __init__(self, inputfile, vocabulary_size=100000, embedding_dim=200, epoch_num=10, batch_size=16, windows_size=5,neg_sample_num=10): 24 | self.op = Options(inputfile, vocabulary_size) 25 | self.embedding_dim = embedding_dim 26 | self.windows_size = windows_size 27 | self.vocabulary_size = vocabulary_size 28 | self.batch_size = batch_size 29 | self.epoch_num = epoch_num 30 | self.neg_sample_num = neg_sample_num 31 | 32 | 33 | def train(self): 34 | model = skipgram(self.vocabulary_size, self.embedding_dim) 35 | if torch.cuda.is_available(): 36 | model.cuda() 37 | optimizer = optim.SGD(model.parameters(),lr=0.2) 38 | for epoch in range(self.epoch_num): 39 | start = time.time() 40 | self.op.process = True 41 | batch_num = 0 42 | batch_new = 0 43 | 44 | while self.op.process: 45 | pos_u, pos_v, neg_v = self.op.generate_batch(self.windows_size, self.batch_size, self.neg_sample_num) 46 | 47 | pos_u = Variable(torch.LongTensor(pos_u)) 48 | pos_v = Variable(torch.LongTensor(pos_v)) 49 | neg_v = Variable(torch.LongTensor(neg_v)) 50 | 51 | 52 | if torch.cuda.is_available(): 53 | pos_u = pos_u.cuda() 54 | pos_v = pos_v.cuda() 55 | neg_v = neg_v.cuda() 56 | 57 | optimizer.zero_grad() 58 | loss = model(pos_u, pos_v, neg_v,self.batch_size) 59 | 60 | loss.backward() 61 | 62 | optimizer.step() 63 | 64 | 65 | if batch_num%30000 == 0: 66 | torch.save(model.state_dict(), './tmp/skipgram.epoch{}.batch{}'.format(epoch,batch_num)) 67 | 68 | if batch_num%2000 == 0: 69 | end = time.time() 70 | word_embeddings = model.input_embeddings() 71 | sp1, sp2 = scorefunction(word_embeddings) 72 | print('eporch,batch=%2d %5d: sp=%1.3f %1.3f pair/sec = %4.2f loss=%4.3f\r'\ 73 | %(epoch, batch_num, sp1, sp2, (batch_num-batch_new)*self.batch_size/(end-start),loss.data[0]),end="") 74 | batch_new = batch_num 75 | start = time.time() 76 | batch_num = batch_num + 1 77 | print() 78 | print("Optimization Finished!") 79 | 80 | 81 | if __name__ == '__main__': 82 | wc= word2vec('text8') 83 | wc.train() 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | -------------------------------------------------------------------------------- /wordsim353/combined.csv: -------------------------------------------------------------------------------- 1 | Word 1,Word 2,Human (mean) 2 | love,sex,6.77 3 | tiger,cat,7.35 4 | tiger,tiger,10.00 5 | book,paper,7.46 6 | computer,keyboard,7.62 7 | computer,internet,7.58 8 | plane,car,5.77 9 | train,car,6.31 10 | telephone,communication,7.50 11 | television,radio,6.77 12 | media,radio,7.42 13 | drug,abuse,6.85 14 | bread,butter,6.19 15 | cucumber,potato,5.92 16 | doctor,nurse,7.00 17 | professor,doctor,6.62 18 | student,professor,6.81 19 | smart,student,4.62 20 | smart,stupid,5.81 21 | company,stock,7.08 22 | stock,market,8.08 23 | stock,phone,1.62 24 | stock,CD,1.31 25 | stock,jaguar,0.92 26 | stock,egg,1.81 27 | fertility,egg,6.69 28 | stock,live,3.73 29 | stock,life,0.92 30 | book,library,7.46 31 | bank,money,8.12 32 | wood,forest,7.73 33 | money,cash,9.15 34 | professor,cucumber,0.31 35 | king,cabbage,0.23 36 | king,queen,8.58 37 | king,rook,5.92 38 | bishop,rabbi,6.69 39 | Jerusalem,Israel,8.46 40 | Jerusalem,Palestinian,7.65 41 | holy,sex,1.62 42 | fuck,sex,9.44 43 | Maradona,football,8.62 44 | football,soccer,9.03 45 | football,basketball,6.81 46 | football,tennis,6.63 47 | tennis,racket,7.56 48 | Arafat,peace,6.73 49 | Arafat,terror,7.65 50 | Arafat,Jackson,2.50 51 | law,lawyer,8.38 52 | movie,star,7.38 53 | movie,popcorn,6.19 54 | movie,critic,6.73 55 | movie,theater,7.92 56 | physics,proton,8.12 57 | physics,chemistry,7.35 58 | space,chemistry,4.88 59 | alcohol,chemistry,5.54 60 | vodka,gin,8.46 61 | vodka,brandy,8.13 62 | drink,car,3.04 63 | drink,ear,1.31 64 | drink,mouth,5.96 65 | drink,eat,6.87 66 | baby,mother,7.85 67 | drink,mother,2.65 68 | car,automobile,8.94 69 | gem,jewel,8.96 70 | journey,voyage,9.29 71 | boy,lad,8.83 72 | coast,shore,9.10 73 | asylum,madhouse,8.87 74 | magician,wizard,9.02 75 | midday,noon,9.29 76 | furnace,stove,8.79 77 | food,fruit,7.52 78 | bird,cock,7.10 79 | bird,crane,7.38 80 | tool,implement,6.46 81 | brother,monk,6.27 82 | crane,implement,2.69 83 | lad,brother,4.46 84 | journey,car,5.85 85 | monk,oracle,5.00 86 | cemetery,woodland,2.08 87 | food,rooster,4.42 88 | coast,hill,4.38 89 | forest,graveyard,1.85 90 | shore,woodland,3.08 91 | monk,slave,0.92 92 | coast,forest,3.15 93 | lad,wizard,0.92 94 | chord,smile,0.54 95 | glass,magician,2.08 96 | noon,string,0.54 97 | rooster,voyage,0.62 98 | money,dollar,8.42 99 | money,cash,9.08 100 | money,currency,9.04 101 | money,wealth,8.27 102 | money,property,7.57 103 | money,possession,7.29 104 | money,bank,8.50 105 | money,deposit,7.73 106 | money,withdrawal,6.88 107 | money,laundering,5.65 108 | money,operation,3.31 109 | tiger,jaguar,8.00 110 | tiger,feline,8.00 111 | tiger,carnivore,7.08 112 | tiger,mammal,6.85 113 | tiger,animal,7.00 114 | tiger,organism,4.77 115 | tiger,fauna,5.62 116 | tiger,zoo,5.87 117 | psychology,psychiatry,8.08 118 | psychology,anxiety,7.00 119 | psychology,fear,6.85 120 | psychology,depression,7.42 121 | psychology,clinic,6.58 122 | psychology,doctor,6.42 123 | psychology,Freud,8.21 124 | psychology,mind,7.69 125 | psychology,health,7.23 126 | psychology,science,6.71 127 | psychology,discipline,5.58 128 | psychology,cognition,7.48 129 | planet,star,8.45 130 | planet,constellation,8.06 131 | planet,moon,8.08 132 | planet,sun,8.02 133 | planet,galaxy,8.11 134 | planet,space,7.92 135 | planet,astronomer,7.94 136 | precedent,example,5.85 137 | precedent,information,3.85 138 | precedent,cognition,2.81 139 | precedent,law,6.65 140 | precedent,collection,2.50 141 | precedent,group,1.77 142 | precedent,antecedent,6.04 143 | cup,coffee,6.58 144 | cup,tableware,6.85 145 | cup,article,2.40 146 | cup,artifact,2.92 147 | cup,object,3.69 148 | cup,entity,2.15 149 | cup,drink,7.25 150 | cup,food,5.00 151 | cup,substance,1.92 152 | cup,liquid,5.90 153 | jaguar,cat,7.42 154 | jaguar,car,7.27 155 | energy,secretary,1.81 156 | secretary,senate,5.06 157 | energy,laboratory,5.09 158 | computer,laboratory,6.78 159 | weapon,secret,6.06 160 | FBI,fingerprint,6.94 161 | FBI,investigation,8.31 162 | investigation,effort,4.59 163 | Mars,water,2.94 164 | Mars,scientist,5.63 165 | news,report,8.16 166 | canyon,landscape,7.53 167 | image,surface,4.56 168 | discovery,space,6.34 169 | water,seepage,6.56 170 | sign,recess,2.38 171 | Wednesday,news,2.22 172 | mile,kilometer,8.66 173 | computer,news,4.47 174 | territory,surface,5.34 175 | atmosphere,landscape,3.69 176 | president,medal,3.00 177 | war,troops,8.13 178 | record,number,6.31 179 | skin,eye,6.22 180 | Japanese,American,6.50 181 | theater,history,3.91 182 | volunteer,motto,2.56 183 | prejudice,recognition,3.00 184 | decoration,valor,5.63 185 | century,year,7.59 186 | century,nation,3.16 187 | delay,racism,1.19 188 | delay,news,3.31 189 | minister,party,6.63 190 | peace,plan,4.75 191 | minority,peace,3.69 192 | attempt,peace,4.25 193 | government,crisis,6.56 194 | deployment,departure,4.25 195 | deployment,withdrawal,5.88 196 | energy,crisis,5.94 197 | announcement,news,7.56 198 | announcement,effort,2.75 199 | stroke,hospital,7.03 200 | disability,death,5.47 201 | victim,emergency,6.47 202 | treatment,recovery,7.91 203 | journal,association,4.97 204 | doctor,personnel,5.00 205 | doctor,liability,5.19 206 | liability,insurance,7.03 207 | school,center,3.44 208 | reason,hypertension,2.31 209 | reason,criterion,5.91 210 | hundred,percent,7.38 211 | Harvard,Yale,8.13 212 | hospital,infrastructure,4.63 213 | death,row,5.25 214 | death,inmate,5.03 215 | lawyer,evidence,6.69 216 | life,death,7.88 217 | life,term,4.50 218 | word,similarity,4.75 219 | board,recommendation,4.47 220 | governor,interview,3.25 221 | OPEC,country,5.63 222 | peace,atmosphere,3.69 223 | peace,insurance,2.94 224 | territory,kilometer,5.28 225 | travel,activity,5.00 226 | competition,price,6.44 227 | consumer,confidence,4.13 228 | consumer,energy,4.75 229 | problem,airport,2.38 230 | car,flight,4.94 231 | credit,card,8.06 232 | credit,information,5.31 233 | hotel,reservation,8.03 234 | grocery,money,5.94 235 | registration,arrangement,6.00 236 | arrangement,accommodation,5.41 237 | month,hotel,1.81 238 | type,kind,8.97 239 | arrival,hotel,6.00 240 | bed,closet,6.72 241 | closet,clothes,8.00 242 | situation,conclusion,4.81 243 | situation,isolation,3.88 244 | impartiality,interest,5.16 245 | direction,combination,2.25 246 | street,place,6.44 247 | street,avenue,8.88 248 | street,block,6.88 249 | street,children,4.94 250 | listing,proximity,2.56 251 | listing,category,6.38 252 | cell,phone,7.81 253 | production,hike,1.75 254 | benchmark,index,4.25 255 | media,trading,3.88 256 | media,gain,2.88 257 | dividend,payment,7.63 258 | dividend,calculation,6.48 259 | calculation,computation,8.44 260 | currency,market,7.50 261 | OPEC,oil,8.59 262 | oil,stock,6.34 263 | announcement,production,3.38 264 | announcement,warning,6.00 265 | profit,warning,3.88 266 | profit,loss,7.63 267 | dollar,yen,7.78 268 | dollar,buck,9.22 269 | dollar,profit,7.38 270 | dollar,loss,6.09 271 | computer,software,8.50 272 | network,hardware,8.31 273 | phone,equipment,7.13 274 | equipment,maker,5.91 275 | luxury,car,6.47 276 | five,month,3.38 277 | report,gain,3.63 278 | investor,earning,7.13 279 | liquid,water,7.89 280 | baseball,season,5.97 281 | game,victory,7.03 282 | game,team,7.69 283 | marathon,sprint,7.47 284 | game,series,6.19 285 | game,defeat,6.97 286 | seven,series,3.56 287 | seafood,sea,7.47 288 | seafood,food,8.34 289 | seafood,lobster,8.70 290 | lobster,food,7.81 291 | lobster,wine,5.70 292 | food,preparation,6.22 293 | video,archive,6.34 294 | start,year,4.06 295 | start,match,4.47 296 | game,round,5.97 297 | boxing,round,7.61 298 | championship,tournament,8.36 299 | fighting,defeating,7.41 300 | line,insurance,2.69 301 | day,summer,3.94 302 | summer,drought,7.16 303 | summer,nature,5.63 304 | day,dawn,7.53 305 | nature,environment,8.31 306 | environment,ecology,8.81 307 | nature,man,6.25 308 | man,woman,8.30 309 | man,governor,5.25 310 | murder,manslaughter,8.53 311 | soap,opera,7.94 312 | opera,performance,6.88 313 | life,lesson,5.94 314 | focus,life,4.06 315 | production,crew,6.25 316 | television,film,7.72 317 | lover,quarrel,6.19 318 | viewer,serial,2.97 319 | possibility,girl,1.94 320 | population,development,3.75 321 | morality,importance,3.31 322 | morality,marriage,3.69 323 | Mexico,Brazil,7.44 324 | gender,equality,6.41 325 | change,attitude,5.44 326 | family,planning,6.25 327 | opera,industry,2.63 328 | sugar,approach,0.88 329 | practice,institution,3.19 330 | ministry,culture,4.69 331 | problem,challenge,6.75 332 | size,prominence,5.31 333 | country,citizen,7.31 334 | planet,people,5.75 335 | development,issue,3.97 336 | experience,music,3.47 337 | music,project,3.63 338 | glass,metal,5.56 339 | aluminum,metal,7.83 340 | chance,credibility,3.88 341 | exhibit,memorabilia,5.31 342 | concert,virtuoso,6.81 343 | rock,jazz,7.59 344 | museum,theater,7.19 345 | observation,architecture,4.38 346 | space,world,6.53 347 | preservation,world,6.19 348 | admission,ticket,7.69 349 | shower,thunderstorm,6.31 350 | shower,flood,6.03 351 | weather,forecast,8.34 352 | disaster,area,6.25 353 | governor,office,6.34 354 | architecture,century,3.78 355 | -------------------------------------------------------------------------------- /wordsim353/combined.tab: -------------------------------------------------------------------------------- 1 | Word 1 Word 2 Human (mean) 2 | love sex 6.77 3 | tiger cat 7.35 4 | tiger tiger 10.00 5 | book paper 7.46 6 | computer keyboard 7.62 7 | computer internet 7.58 8 | plane car 5.77 9 | train car 6.31 10 | telephone communication 7.50 11 | television radio 6.77 12 | media radio 7.42 13 | drug abuse 6.85 14 | bread butter 6.19 15 | cucumber potato 5.92 16 | doctor nurse 7.00 17 | professor doctor 6.62 18 | student professor 6.81 19 | smart student 4.62 20 | smart stupid 5.81 21 | company stock 7.08 22 | stock market 8.08 23 | stock phone 1.62 24 | stock CD 1.31 25 | stock jaguar 0.92 26 | stock egg 1.81 27 | fertility egg 6.69 28 | stock live 3.73 29 | stock life 0.92 30 | book library 7.46 31 | bank money 8.12 32 | wood forest 7.73 33 | money cash 9.15 34 | professor cucumber 0.31 35 | king cabbage 0.23 36 | king queen 8.58 37 | king rook 5.92 38 | bishop rabbi 6.69 39 | Jerusalem Israel 8.46 40 | Jerusalem Palestinian 7.65 41 | holy sex 1.62 42 | fuck sex 9.44 43 | Maradona football 8.62 44 | football soccer 9.03 45 | football basketball 6.81 46 | football tennis 6.63 47 | tennis racket 7.56 48 | Arafat peace 6.73 49 | Arafat terror 7.65 50 | Arafat Jackson 2.50 51 | law lawyer 8.38 52 | movie star 7.38 53 | movie popcorn 6.19 54 | movie critic 6.73 55 | movie theater 7.92 56 | physics proton 8.12 57 | physics chemistry 7.35 58 | space chemistry 4.88 59 | alcohol chemistry 5.54 60 | vodka gin 8.46 61 | vodka brandy 8.13 62 | drink car 3.04 63 | drink ear 1.31 64 | drink mouth 5.96 65 | drink eat 6.87 66 | baby mother 7.85 67 | drink mother 2.65 68 | car automobile 8.94 69 | gem jewel 8.96 70 | journey voyage 9.29 71 | boy lad 8.83 72 | coast shore 9.10 73 | asylum madhouse 8.87 74 | magician wizard 9.02 75 | midday noon 9.29 76 | furnace stove 8.79 77 | food fruit 7.52 78 | bird cock 7.10 79 | bird crane 7.38 80 | tool implement 6.46 81 | brother monk 6.27 82 | crane implement 2.69 83 | lad brother 4.46 84 | journey car 5.85 85 | monk oracle 5.00 86 | cemetery woodland 2.08 87 | food rooster 4.42 88 | coast hill 4.38 89 | forest graveyard 1.85 90 | shore woodland 3.08 91 | monk slave 0.92 92 | coast forest 3.15 93 | lad wizard 0.92 94 | chord smile 0.54 95 | glass magician 2.08 96 | noon string 0.54 97 | rooster voyage 0.62 98 | money dollar 8.42 99 | money cash 9.08 100 | money currency 9.04 101 | money wealth 8.27 102 | money property 7.57 103 | money possession 7.29 104 | money bank 8.50 105 | money deposit 7.73 106 | money withdrawal 6.88 107 | money laundering 5.65 108 | money operation 3.31 109 | tiger jaguar 8.00 110 | tiger feline 8.00 111 | tiger carnivore 7.08 112 | tiger mammal 6.85 113 | tiger animal 7.00 114 | tiger organism 4.77 115 | tiger fauna 5.62 116 | tiger zoo 5.87 117 | psychology psychiatry 8.08 118 | psychology anxiety 7.00 119 | psychology fear 6.85 120 | psychology depression 7.42 121 | psychology clinic 6.58 122 | psychology doctor 6.42 123 | psychology Freud 8.21 124 | psychology mind 7.69 125 | psychology health 7.23 126 | psychology science 6.71 127 | psychology discipline 5.58 128 | psychology cognition 7.48 129 | planet star 8.45 130 | planet constellation 8.06 131 | planet moon 8.08 132 | planet sun 8.02 133 | planet galaxy 8.11 134 | planet space 7.92 135 | planet astronomer 7.94 136 | precedent example 5.85 137 | precedent information 3.85 138 | precedent cognition 2.81 139 | precedent law 6.65 140 | precedent collection 2.50 141 | precedent group 1.77 142 | precedent antecedent 6.04 143 | cup coffee 6.58 144 | cup tableware 6.85 145 | cup article 2.40 146 | cup artifact 2.92 147 | cup object 3.69 148 | cup entity 2.15 149 | cup drink 7.25 150 | cup food 5.00 151 | cup substance 1.92 152 | cup liquid 5.90 153 | jaguar cat 7.42 154 | jaguar car 7.27 155 | energy secretary 1.81 156 | secretary senate 5.06 157 | energy laboratory 5.09 158 | computer laboratory 6.78 159 | weapon secret 6.06 160 | FBI fingerprint 6.94 161 | FBI investigation 8.31 162 | investigation effort 4.59 163 | Mars water 2.94 164 | Mars scientist 5.63 165 | news report 8.16 166 | canyon landscape 7.53 167 | image surface 4.56 168 | discovery space 6.34 169 | water seepage 6.56 170 | sign recess 2.38 171 | Wednesday news 2.22 172 | mile kilometer 8.66 173 | computer news 4.47 174 | territory surface 5.34 175 | atmosphere landscape 3.69 176 | president medal 3.00 177 | war troops 8.13 178 | record number 6.31 179 | skin eye 6.22 180 | Japanese American 6.50 181 | theater history 3.91 182 | volunteer motto 2.56 183 | prejudice recognition 3.00 184 | decoration valor 5.63 185 | century year 7.59 186 | century nation 3.16 187 | delay racism 1.19 188 | delay news 3.31 189 | minister party 6.63 190 | peace plan 4.75 191 | minority peace 3.69 192 | attempt peace 4.25 193 | government crisis 6.56 194 | deployment departure 4.25 195 | deployment withdrawal 5.88 196 | energy crisis 5.94 197 | announcement news 7.56 198 | announcement effort 2.75 199 | stroke hospital 7.03 200 | disability death 5.47 201 | victim emergency 6.47 202 | treatment recovery 7.91 203 | journal association 4.97 204 | doctor personnel 5.00 205 | doctor liability 5.19 206 | liability insurance 7.03 207 | school center 3.44 208 | reason hypertension 2.31 209 | reason criterion 5.91 210 | hundred percent 7.38 211 | Harvard Yale 8.13 212 | hospital infrastructure 4.63 213 | death row 5.25 214 | death inmate 5.03 215 | lawyer evidence 6.69 216 | life death 7.88 217 | life term 4.50 218 | word similarity 4.75 219 | board recommendation 4.47 220 | governor interview 3.25 221 | OPEC country 5.63 222 | peace atmosphere 3.69 223 | peace insurance 2.94 224 | territory kilometer 5.28 225 | travel activity 5.00 226 | competition price 6.44 227 | consumer confidence 4.13 228 | consumer energy 4.75 229 | problem airport 2.38 230 | car flight 4.94 231 | credit card 8.06 232 | credit information 5.31 233 | hotel reservation 8.03 234 | grocery money 5.94 235 | registration arrangement 6.00 236 | arrangement accommodation 5.41 237 | month hotel 1.81 238 | type kind 8.97 239 | arrival hotel 6.00 240 | bed closet 6.72 241 | closet clothes 8.00 242 | situation conclusion 4.81 243 | situation isolation 3.88 244 | impartiality interest 5.16 245 | direction combination 2.25 246 | street place 6.44 247 | street avenue 8.88 248 | street block 6.88 249 | street children 4.94 250 | listing proximity 2.56 251 | listing category 6.38 252 | cell phone 7.81 253 | production hike 1.75 254 | benchmark index 4.25 255 | media trading 3.88 256 | media gain 2.88 257 | dividend payment 7.63 258 | dividend calculation 6.48 259 | calculation computation 8.44 260 | currency market 7.50 261 | OPEC oil 8.59 262 | oil stock 6.34 263 | announcement production 3.38 264 | announcement warning 6.00 265 | profit warning 3.88 266 | profit loss 7.63 267 | dollar yen 7.78 268 | dollar buck 9.22 269 | dollar profit 7.38 270 | dollar loss 6.09 271 | computer software 8.50 272 | network hardware 8.31 273 | phone equipment 7.13 274 | equipment maker 5.91 275 | luxury car 6.47 276 | five month 3.38 277 | report gain 3.63 278 | investor earning 7.13 279 | liquid water 7.89 280 | baseball season 5.97 281 | game victory 7.03 282 | game team 7.69 283 | marathon sprint 7.47 284 | game series 6.19 285 | game defeat 6.97 286 | seven series 3.56 287 | seafood sea 7.47 288 | seafood food 8.34 289 | seafood lobster 8.70 290 | lobster food 7.81 291 | lobster wine 5.70 292 | food preparation 6.22 293 | video archive 6.34 294 | start year 4.06 295 | start match 4.47 296 | game round 5.97 297 | boxing round 7.61 298 | championship tournament 8.36 299 | fighting defeating 7.41 300 | line insurance 2.69 301 | day summer 3.94 302 | summer drought 7.16 303 | summer nature 5.63 304 | day dawn 7.53 305 | nature environment 8.31 306 | environment ecology 8.81 307 | nature man 6.25 308 | man woman 8.30 309 | man governor 5.25 310 | murder manslaughter 8.53 311 | soap opera 7.94 312 | opera performance 6.88 313 | life lesson 5.94 314 | focus life 4.06 315 | production crew 6.25 316 | television film 7.72 317 | lover quarrel 6.19 318 | viewer serial 2.97 319 | possibility girl 1.94 320 | population development 3.75 321 | morality importance 3.31 322 | morality marriage 3.69 323 | Mexico Brazil 7.44 324 | gender equality 6.41 325 | change attitude 5.44 326 | family planning 6.25 327 | opera industry 2.63 328 | sugar approach 0.88 329 | practice institution 3.19 330 | ministry culture 4.69 331 | problem challenge 6.75 332 | size prominence 5.31 333 | country citizen 7.31 334 | planet people 5.75 335 | development issue 3.97 336 | experience music 3.47 337 | music project 3.63 338 | glass metal 5.56 339 | aluminum metal 7.83 340 | chance credibility 3.88 341 | exhibit memorabilia 5.31 342 | concert virtuoso 6.81 343 | rock jazz 7.59 344 | museum theater 7.19 345 | observation architecture 4.38 346 | space world 6.53 347 | preservation world 6.19 348 | admission ticket 7.69 349 | shower thunderstorm 6.31 350 | shower flood 6.03 351 | weather forecast 8.34 352 | disaster area 6.25 353 | governor office 6.34 354 | architecture century 3.78 355 | -------------------------------------------------------------------------------- /wordsim353/instructions.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fanglanting/skip-gram-pytorch/0a16cd6b03f56ebca1854c4b07368ea826625d0f/wordsim353/instructions.txt -------------------------------------------------------------------------------- /wordsim353/set1.csv: -------------------------------------------------------------------------------- 1 | Word 1,Word 2,Human (mean),1,2,3,4,5,6,7,8,9,10,11,12,13 2 | love,sex,6.77,9,6,8,8,7,8,8,4,7,2,6,7,8 3 | tiger,cat,7.35,9,7,8,7,8,9,8.5,5,6,9,7,5,7 4 | tiger,tiger,10.00,10,10,10,10,10,10,10,10,10,10,10,10,10 5 | book,paper,7.46,8,8,7,7,8,9,7,6,7,8,9,4,9 6 | computer,keyboard,7.62,8,7,9,9,8,8,7,7,6,8,10,3,9 7 | computer,internet,7.58,8,6,9,8,8,8,7.5,7,7,7,9,5,9 8 | plane,car,5.77,6,6,7,5,3,6,7,6,6,6,7,3,7 9 | train,car,6.31,7,7.5,7.5,5,3,6,7,6,6,6,9,4,8 10 | telephone,communication,7.50,7,6.5,8,8,6,8,8,7,5,9,9,8,8 11 | television,radio,6.77,7,7.5,9,7,3,6,7,8,5.5,6,8,6,8 12 | media,radio,7.42,7,7,8.5,9,6,7,7,7,5,7,10,8,8 13 | drug,abuse,6.85,7,5.5,8,10,7,9,7,7,4,5,8.5,4,7 14 | bread,butter,6.19,6,5.5,8,9,6,8,7,5,6,4,4,3,9 15 | cucumber,potato,5.92,7,7.5,7,6,4,6,6.5,4,6,4,5,6,8 16 | doctor,nurse,7.00,7,8,9,7,5,7,7,7,6,6,7,7,8 17 | professor,doctor,6.62,6,7.5,8,7,4,6,8.5,6,7,3,6,9,8 18 | student,professor,6.81,6,8,9,6,4,8,7.5,8,6,3,8,7,8 19 | smart,student,4.62,5,6,5,2,4,6,5,7,4,3,3,5,5 20 | smart,stupid,5.81,3,7,9,9,5,8,6,0,6.5,3,5,7,7 21 | company,stock,7.08,6,8,9,9,4,8,8,6,6,8,6,6,8 22 | stock,market,8.08,8,9,9.5,8,5,9,9,9,7,8,7.5,7,9 23 | stock,phone,1.62,3,1,0,1,4,3,1,1,1,3,0,2,1 24 | stock,CD,1.31,2,1,0,1,4,1,0,0,1,3,3,1,0 25 | stock,jaguar,0.92,1,0,0,1,4,0,2,0,1,3,0,0,0 26 | stock,egg,1.81,5,1.5,0,1,3,0,0,2,2,3,1,5,0 27 | fertility,egg,6.69,7,8,8,7,4,8,8,8,6,9,2,6,6 28 | stock,live,3.73,8,5.5,6,1,4,5,0,0,1,6,2,3,7 29 | stock,life,0.92,4,0,0,1,3,0,0,0,2,0,0,0,2 30 | book,library,7.46,8,9,8,9,5,9,8,7,6,8,7,6,7 31 | bank,money,8.12,8,9,9.5,9,5,9,8,9,6,9,9,8,7 32 | wood,forest,7.73,9,6,9.5,7,5,9,9,9,6,8,9,8,6 33 | money,cash,9.15,10,9.5,9.5,10,8,9,9.5,10,7,10,8.5,9,9 34 | professor,cucumber,0.31,1,0,0,1,2,0,0,0,0,0,0,0,0 35 | king,cabbage,0.23,1,0,0,1,1,0,0,0,0,0,0,0,0 36 | king,queen,8.58,9,9.5,9.5,10,7,8,8.5,9,8,8,8,8,9 37 | king,rook,5.92,7,7.5,7,6,7,8,8.5,0,8,0,6,5,7 38 | bishop,rabbi,6.69,7,7.5,8.5,2,5,7,9,7,8,7,6,7,6 39 | Jerusalem,Israel,8.46,9,8,9.5,9,8,8,8,8,9,8,9.5,7,9 40 | Jerusalem,Palestinian,7.65,9,8,9,8,4,8,8,7,9,8,9.5,5,7 41 | holy,sex,1.62,3,0,5,2,1,1,7,0,1,0,0,0,1 42 | fuck,sex,9.44,10,9.75,10,10,8,9,9,10,9,10,8,10,10 43 | Maradona,football,8.62,9,9,9.5,10,7,9,8.5,8,9,10,9,6,8 44 | football,soccer,9.03,9,9.9,9,10,8,7,9.5,10,8,10,9,9,9 45 | football,basketball,6.81,8,7.5,8.5,3,3,8,8,6,7.5,8,7,6,8 46 | football,tennis,6.63,7,7.25,8.5,3,3,7,8,6,7.5,8,7,6,8 47 | tennis,racket,7.56,4,8,9.5,9,4,9,7.5,8,7.8,8,8.5,6,9 48 | Arafat,peace,6.73,8,8,9.5,9,2,8,7,7,7,5,7,4,6 49 | Arafat,terror,7.65,8,8,9.5,9,5,9,7,7,8,10,8,4,7 50 | Arafat,Jackson,2.50,4,7.5,0,2,3,1,0,0,4,1,6,2,2 51 | law,lawyer,8.38,9,8,9.5,9,6,9,9.5,9,7,10,6,8,9 52 | movie,star,7.38,9,8,9.5,8,6,9,7,8,7,5,6.5,5,8 53 | movie,popcorn,6.19,7,6,9,4,5,7,8,9,6,4,6.5,2,7 54 | movie,critic,6.73,8,7.5,9.5,9,6,8,7.5,8,5,4,5,3,7 55 | movie,theater,7.92,8,8,9.5,9,6,8,8.5,7,7,10,6,7,9 56 | physics,proton,8.12,9,8.5,9,10,6,8,8.5,8,7,8,9.5,5,9 57 | physics,chemistry,7.35,8,8.5,9,8,5,7,8,7,8,7,7,4,9 58 | space,chemistry,4.88,6,8,3,5,5,6,7.5,6,5,3,1,2,6 59 | alcohol,chemistry,5.54,8,8,7,5,5,8,6,4,4,2,6,5,4 60 | vodka,gin,8.46,9,9.5,9,10,7,8,8.5,9,8,10,6,8,8 61 | vodka,brandy,8.13,9,9.25,9,7,7,8,8.5,9,8,10,6,7,8 62 | drink,car,3.04,7,0.5,0,2,2,7,5,5,4,0,2,0,5 63 | drink,ear,1.31,3,0,0,5,2,2,2,0,1,1,0,0,1 64 | drink,mouth,5.96,8,6,7,7,3,7,4,6,7.5,6,6,2,8 65 | drink,eat,6.87,8,8.75,9,9,3,7,8,9,7.5,0,5,7,8 66 | baby,mother,7.85,9,9,9,9,5,8,7,8,8,10,8,3,9 67 | drink,mother,2.65,3,1,1,3,3,7,0,2,6.5,0,4,1,3 68 | car,automobile,8.94,9,9.75,10,10,5,6,10,10,7.5,10,10,10,9 69 | gem,jewel,8.96,9,9.5,10,10,6,8,8.5,10,7.5,10,10,8,10 70 | journey,voyage,9.29,9,9.75,10,10,6,7,9.5,10,9.5,10,10,10,10 71 | boy,lad,8.83,9,9.75,10,10,6,5,9.5,9,7.5,10,10,9,10 72 | coast,shore,9.10,9,9.75,10,10,6,6,10,8,9.5,10,10,10,10 73 | asylum,madhouse,8.87,9,9.75,7,10,6,7,9.5,10,9,10,10,9,9 74 | magician,wizard,9.02,9,9.75,10,10,7,6,9,8,8.5,10,10,10,10 75 | midday,noon,9.29,10,9.75,9,10,7,6,9.5,10,9.5,10,10,10,10 76 | furnace,stove,8.79,9,9.75,9.5,10,7,7,9,9,8,10,10,8,8 77 | food,fruit,7.52,8,8.75,8,8,5,7,8,7,7,9,8,7,7 78 | bird,cock,7.10,8,8.5,8,7,4,7,7,6,6.8,9,8,7,6 79 | bird,crane,7.38,9,8.5,8.5,7,4,7,7,7,7,9,8,7,7 80 | tool,implement,6.46,8,6,8,7,4,7,6,6,5,6,10,7,4 81 | brother,monk,6.27,8,7,8,8,5,7,8.5,7,5,0,8,5,5 82 | crane,implement,2.69,3,6,1,1,4,1,0,6,1,0,9,3,0 83 | lad,brother,4.46,8,5.5,5,2,4,3,7,4,2.5,7,5,2,3 84 | journey,car,5.85,7,7,7,6,4,6,6,7,5,5,5,4,7 85 | monk,oracle,5.00,7,8,3,4,4,6,5,8,6,3,4,6,1 86 | cemetery,woodland,2.08,3,2,1,2,3,6,2,3,3,0,0,1,1 87 | food,rooster,4.42,7,4,4,6,3,6,7,2,4.5,2,8,1,3 88 | coast,hill,4.38,6,6,6,5,2,6,5,5,4,3,4,1,4 89 | forest,graveyard,1.85,4,2,1,1,2,6,1,3,3,0,0,1,0 90 | shore,woodland,3.08,6,6,1,1,2,6,5,4,4,3,0,1,1 91 | monk,slave,0.92,3,2,1,1,2,2,0,0,0,0,0,1,0 92 | coast,forest,3.15,6,6,1,1,2,6,5,4,4,3,1,1,1 93 | lad,wizard,0.92,4,0,0,1,2,3,0,0,0,0,0,1,1 94 | chord,smile,0.54,3,0,0,1,2,1,0,0,0,0,0,0,0 95 | glass,magician,2.08,4,1,4,2,2,3,0,0,0,0,10,0,1 96 | noon,string,0.54,2,0,0,1,2,1,0,0,1,0,0,0,0 97 | rooster,voyage,0.62,2,0,0,1,2,1,0,0,1,0,1,0,0 98 | money,dollar,8.42,9,9.5,9,10,5,8,8.5,8,8,10,8.5,8,8 99 | money,cash,9.08,10,9.5,9.5,10,5,9,9.5,10,8,10,8.5,9,10 100 | money,currency,9.04,10,9.5,9,10,5,9,9.5,9,9,10,8.5,9,10 101 | money,wealth,8.27,9,8,9,9,5,6,8.5,9,9,10,8,9,8 102 | money,property,7.57,8,8.25,6,8,5,8,8,7,8.2,8,8,7,9 103 | money,possession,7.29,8,8.25,7,7,5,7,7.5,5,9,7,8,7,9 104 | money,bank,8.50,9,8,9.5,9,6,9,8.5,9,8.5,10,8,7,9 105 | money,deposit,7.73,9,8,9.5,9,5,9,8,7,7,8,7,7,7 106 | money,withdrawal,6.88,8,8,9,9,5,9,8,5,6.5,8,2,5,7 107 | money,laundering,5.65,8,7,8,7,5,7,7.5,2,5,5,5,0,7 108 | money,operation,3.31,4,2,3,5,5,5,2,2,4,3,5,1,2 109 | tiger,jaguar,8.00,9,9,9,10,5,8,7.5,6,8,9,8.5,7,8 110 | tiger,feline,8.00,9,7.5,9.5,8,5,8,8.5,8,8,9,8.5,7,8 111 | tiger,carnivore,7.08,9,6,8,5,5,8,7,7,8.1,8,6,7,8 112 | tiger,mammal,6.85,9,7,7.5,5,5,7,7,7,8,8,8.5,6,4 113 | tiger,animal,7.00,8,7,7.5,5,5,6,6,7,7.5,9,10,5,8 114 | tiger,organism,4.77,8,7,6,1,5,5,1,2,6,4,10,5,2 115 | tiger,fauna,5.62,8,7,7.5,1,2,6,7,2,5.5,9,10,5,3 116 | tiger,zoo,5.87,8,5.25,8,3,5,7,6,8,6,5,5,5,5 117 | psychology,psychiatry,8.08,9,8.5,9.5,9,4,8,8,8,7,9,9,8,8 118 | psychology,anxiety,7.00,7,7,8.5,4,5,8,5,7,8,8,8.5,7,8 119 | psychology,fear,6.85,8,7,8.5,4,5,8,5,5,8,8,8.5,7,7 120 | psychology,depression,7.42,9,8,9,5,5,8,5,7,8,8,8.5,7,9 121 | psychology,clinic,6.58,8,8,9.5,5,4,9,7,6,6,7,6,4,6 122 | psychology,doctor,6.42,9,8,9,5,5,8,7.5,6,5,5,7,4,5 123 | psychology,Freud,8.21,9,9.25,9.5,10,5,8,8,9,7.5,9,8.5,7,7 124 | psychology,mind,7.69,9,9.5,9,9,5,8,5,8,7,8,8.5,7,7 125 | psychology,health,7.23,9,8,8.5,5,5,7,5,8,8,8,8.5,6,8 126 | psychology,science,6.71,8,7.75,7.5,5,5,7,4,8,6.5,7,9.5,4,8 127 | psychology,discipline,5.58,8,7,7.5,6,4,6,4,7,6,8,2,5,2 128 | psychology,cognition,7.48,9,9.75,8.5,6,3,8,8,8,6.5,9,7.5,8,6 129 | planet,star,8.45,9,9.9,10,10,5,8,8.5,9,8,9,8.5,7,8 130 | planet,constellation,8.06,9,8.25,9,9,6,8,8,8,8,9,8.5,6,8 131 | planet,moon,8.08,9,8.5,9,9,5,8,7,9,8,10,8.5,7,7 132 | planet,sun,8.02,9,8.75,9,8,5,8,7,9,8,10,8.5,7,7 133 | planet,galaxy,8.11,9,8.25,9.5,8,5,8,8,8,8.2,10,9.5,6,8 134 | planet,space,7.92,9,8,9.5,6,5,8,7,8,8,10,9.5,6,9 135 | planet,astronomer,7.94,9,8.25,9.5,8,5,8,7,7,8,10,7.5,7,9 136 | precedent,example,5.85,6,8.5,9.5,10,3,7,6,8,1,1,9,2,5 137 | precedent,information,3.85,5,5.5,6,8,4,5,1,2,0,1,7.5,2,3 138 | precedent,cognition,2.81,6,5.5,2,7,3,3,0,0,0,1,7,1,1 139 | precedent,law,6.65,8,7,8.5,8,3,8,7,5,7.5,8,8.5,5,3 140 | precedent,collection,2.50,7,5.5,1,3,3,5,0,0,0,0,6,1,1 141 | precedent,group,1.77,6,1,1,2,3,5,0,0,0,0,4,1,0 142 | precedent,antecedent,6.04,9.5,0,9.5,9,4,7,7.5,7,8,7,5,3,2 143 | cup,coffee,6.58,9,8,9,8,5,9,8,5,6.5,5,4,3,6 144 | cup,tableware,6.85,7,8.5,8,9,5,7,7,4,5,9,8.5,5,6 145 | cup,article,2.40,1,8.25,6,3,3,0,0,0,0,3,3,2,2 146 | cup,artifact,2.92,7,8,1,2,4,0,2,1,5,3,4,0,1 147 | cup,object,3.69,8,8,4,2,5,3,2,5,5,0,3,2,1 148 | cup,entity,2.15,3,6,3,1,4,3,0,3,4,0,1,0,0 149 | cup,drink,7.25,9,7.75,9,8,4,8,6,8,8,6,7.5,6,7 150 | cup,food,5.00,7,7,6,2,3,7,3,7,6,4,4,4,5 151 | cup,substance,1.92,3,3,2,1,3,2,1,3,5,0,2,0,0 152 | cup,liquid,5.90,9,7.75,7,5,4,7,4,7,7,6,7,4,2 153 | jaguar,cat,7.42,9,7,8,8,4,8,7.5,7,7,9,7,7,8 154 | jaguar,car,7.27,9,9,8.5,8,4,8,7,7,8,9,4,5,8 155 | -------------------------------------------------------------------------------- /wordsim353/set1.tab: -------------------------------------------------------------------------------- 1 | Word 1 Word 2 Human (mean) 1 2 3 4 5 6 7 8 9 10 11 12 13 2 | love sex 6.77 9 6 8 8 7 8 8 4 7 2 6 7 8 3 | tiger cat 7.35 9 7 8 7 8 9 8.5 5 6 9 7 5 7 4 | tiger tiger 10.00 10 10 10 10 10 10 10 10 10 10 10 10 10 5 | book paper 7.46 8 8 7 7 8 9 7 6 7 8 9 4 9 6 | computer keyboard 7.62 8 7 9 9 8 8 7 7 6 8 10 3 9 7 | computer internet 7.58 8 6 9 8 8 8 7.5 7 7 7 9 5 9 8 | plane car 5.77 6 6 7 5 3 6 7 6 6 6 7 3 7 9 | train car 6.31 7 7.5 7.5 5 3 6 7 6 6 6 9 4 8 10 | telephone communication 7.50 7 6.5 8 8 6 8 8 7 5 9 9 8 8 11 | television radio 6.77 7 7.5 9 7 3 6 7 8 5.5 6 8 6 8 12 | media radio 7.42 7 7 8.5 9 6 7 7 7 5 7 10 8 8 13 | drug abuse 6.85 7 5.5 8 10 7 9 7 7 4 5 8.5 4 7 14 | bread butter 6.19 6 5.5 8 9 6 8 7 5 6 4 4 3 9 15 | cucumber potato 5.92 7 7.5 7 6 4 6 6.5 4 6 4 5 6 8 16 | doctor nurse 7.00 7 8 9 7 5 7 7 7 6 6 7 7 8 17 | professor doctor 6.62 6 7.5 8 7 4 6 8.5 6 7 3 6 9 8 18 | student professor 6.81 6 8 9 6 4 8 7.5 8 6 3 8 7 8 19 | smart student 4.62 5 6 5 2 4 6 5 7 4 3 3 5 5 20 | smart stupid 5.81 3 7 9 9 5 8 6 0 6.5 3 5 7 7 21 | company stock 7.08 6 8 9 9 4 8 8 6 6 8 6 6 8 22 | stock market 8.08 8 9 9.5 8 5 9 9 9 7 8 7.5 7 9 23 | stock phone 1.62 3 1 0 1 4 3 1 1 1 3 0 2 1 24 | stock CD 1.31 2 1 0 1 4 1 0 0 1 3 3 1 0 25 | stock jaguar 0.92 1 0 0 1 4 0 2 0 1 3 0 0 0 26 | stock egg 1.81 5 1.5 0 1 3 0 0 2 2 3 1 5 0 27 | fertility egg 6.69 7 8 8 7 4 8 8 8 6 9 2 6 6 28 | stock live 3.73 8 5.5 6 1 4 5 0 0 1 6 2 3 7 29 | stock life 0.92 4 0 0 1 3 0 0 0 2 0 0 0 2 30 | book library 7.46 8 9 8 9 5 9 8 7 6 8 7 6 7 31 | bank money 8.12 8 9 9.5 9 5 9 8 9 6 9 9 8 7 32 | wood forest 7.73 9 6 9.5 7 5 9 9 9 6 8 9 8 6 33 | money cash 9.15 10 9.5 9.5 10 8 9 9.5 10 7 10 8.5 9 9 34 | professor cucumber 0.31 1 0 0 1 2 0 0 0 0 0 0 0 0 35 | king cabbage 0.23 1 0 0 1 1 0 0 0 0 0 0 0 0 36 | king queen 8.58 9 9.5 9.5 10 7 8 8.5 9 8 8 8 8 9 37 | king rook 5.92 7 7.5 7 6 7 8 8.5 0 8 0 6 5 7 38 | bishop rabbi 6.69 7 7.5 8.5 2 5 7 9 7 8 7 6 7 6 39 | Jerusalem Israel 8.46 9 8 9.5 9 8 8 8 8 9 8 9.5 7 9 40 | Jerusalem Palestinian 7.65 9 8 9 8 4 8 8 7 9 8 9.5 5 7 41 | holy sex 1.62 3 0 5 2 1 1 7 0 1 0 0 0 1 42 | fuck sex 9.44 10 9.75 10 10 8 9 9 10 9 10 8 10 10 43 | Maradona football 8.62 9 9 9.5 10 7 9 8.5 8 9 10 9 6 8 44 | football soccer 9.03 9 9.9 9 10 8 7 9.5 10 8 10 9 9 9 45 | football basketball 6.81 8 7.5 8.5 3 3 8 8 6 7.5 8 7 6 8 46 | football tennis 6.63 7 7.25 8.5 3 3 7 8 6 7.5 8 7 6 8 47 | tennis racket 7.56 4 8 9.5 9 4 9 7.5 8 7.8 8 8.5 6 9 48 | Arafat peace 6.73 8 8 9.5 9 2 8 7 7 7 5 7 4 6 49 | Arafat terror 7.65 8 8 9.5 9 5 9 7 7 8 10 8 4 7 50 | Arafat Jackson 2.50 4 7.5 0 2 3 1 0 0 4 1 6 2 2 51 | law lawyer 8.38 9 8 9.5 9 6 9 9.5 9 7 10 6 8 9 52 | movie star 7.38 9 8 9.5 8 6 9 7 8 7 5 6.5 5 8 53 | movie popcorn 6.19 7 6 9 4 5 7 8 9 6 4 6.5 2 7 54 | movie critic 6.73 8 7.5 9.5 9 6 8 7.5 8 5 4 5 3 7 55 | movie theater 7.92 8 8 9.5 9 6 8 8.5 7 7 10 6 7 9 56 | physics proton 8.12 9 8.5 9 10 6 8 8.5 8 7 8 9.5 5 9 57 | physics chemistry 7.35 8 8.5 9 8 5 7 8 7 8 7 7 4 9 58 | space chemistry 4.88 6 8 3 5 5 6 7.5 6 5 3 1 2 6 59 | alcohol chemistry 5.54 8 8 7 5 5 8 6 4 4 2 6 5 4 60 | vodka gin 8.46 9 9.5 9 10 7 8 8.5 9 8 10 6 8 8 61 | vodka brandy 8.13 9 9.25 9 7 7 8 8.5 9 8 10 6 7 8 62 | drink car 3.04 7 0.5 0 2 2 7 5 5 4 0 2 0 5 63 | drink ear 1.31 3 0 0 5 2 2 2 0 1 1 0 0 1 64 | drink mouth 5.96 8 6 7 7 3 7 4 6 7.5 6 6 2 8 65 | drink eat 6.87 8 8.75 9 9 3 7 8 9 7.5 0 5 7 8 66 | baby mother 7.85 9 9 9 9 5 8 7 8 8 10 8 3 9 67 | drink mother 2.65 3 1 1 3 3 7 0 2 6.5 0 4 1 3 68 | car automobile 8.94 9 9.75 10 10 5 6 10 10 7.5 10 10 10 9 69 | gem jewel 8.96 9 9.5 10 10 6 8 8.5 10 7.5 10 10 8 10 70 | journey voyage 9.29 9 9.75 10 10 6 7 9.5 10 9.5 10 10 10 10 71 | boy lad 8.83 9 9.75 10 10 6 5 9.5 9 7.5 10 10 9 10 72 | coast shore 9.10 9 9.75 10 10 6 6 10 8 9.5 10 10 10 10 73 | asylum madhouse 8.87 9 9.75 7 10 6 7 9.5 10 9 10 10 9 9 74 | magician wizard 9.02 9 9.75 10 10 7 6 9 8 8.5 10 10 10 10 75 | midday noon 9.29 10 9.75 9 10 7 6 9.5 10 9.5 10 10 10 10 76 | furnace stove 8.79 9 9.75 9.5 10 7 7 9 9 8 10 10 8 8 77 | food fruit 7.52 8 8.75 8 8 5 7 8 7 7 9 8 7 7 78 | bird cock 7.10 8 8.5 8 7 4 7 7 6 6.8 9 8 7 6 79 | bird crane 7.38 9 8.5 8.5 7 4 7 7 7 7 9 8 7 7 80 | tool implement 6.46 8 6 8 7 4 7 6 6 5 6 10 7 4 81 | brother monk 6.27 8 7 8 8 5 7 8.5 7 5 0 8 5 5 82 | crane implement 2.69 3 6 1 1 4 1 0 6 1 0 9 3 0 83 | lad brother 4.46 8 5.5 5 2 4 3 7 4 2.5 7 5 2 3 84 | journey car 5.85 7 7 7 6 4 6 6 7 5 5 5 4 7 85 | monk oracle 5.00 7 8 3 4 4 6 5 8 6 3 4 6 1 86 | cemetery woodland 2.08 3 2 1 2 3 6 2 3 3 0 0 1 1 87 | food rooster 4.42 7 4 4 6 3 6 7 2 4.5 2 8 1 3 88 | coast hill 4.38 6 6 6 5 2 6 5 5 4 3 4 1 4 89 | forest graveyard 1.85 4 2 1 1 2 6 1 3 3 0 0 1 0 90 | shore woodland 3.08 6 6 1 1 2 6 5 4 4 3 0 1 1 91 | monk slave 0.92 3 2 1 1 2 2 0 0 0 0 0 1 0 92 | coast forest 3.15 6 6 1 1 2 6 5 4 4 3 1 1 1 93 | lad wizard 0.92 4 0 0 1 2 3 0 0 0 0 0 1 1 94 | chord smile 0.54 3 0 0 1 2 1 0 0 0 0 0 0 0 95 | glass magician 2.08 4 1 4 2 2 3 0 0 0 0 10 0 1 96 | noon string 0.54 2 0 0 1 2 1 0 0 1 0 0 0 0 97 | rooster voyage 0.62 2 0 0 1 2 1 0 0 1 0 1 0 0 98 | money dollar 8.42 9 9.5 9 10 5 8 8.5 8 8 10 8.5 8 8 99 | money cash 9.08 10 9.5 9.5 10 5 9 9.5 10 8 10 8.5 9 10 100 | money currency 9.04 10 9.5 9 10 5 9 9.5 9 9 10 8.5 9 10 101 | money wealth 8.27 9 8 9 9 5 6 8.5 9 9 10 8 9 8 102 | money property 7.57 8 8.25 6 8 5 8 8 7 8.2 8 8 7 9 103 | money possession 7.29 8 8.25 7 7 5 7 7.5 5 9 7 8 7 9 104 | money bank 8.50 9 8 9.5 9 6 9 8.5 9 8.5 10 8 7 9 105 | money deposit 7.73 9 8 9.5 9 5 9 8 7 7 8 7 7 7 106 | money withdrawal 6.88 8 8 9 9 5 9 8 5 6.5 8 2 5 7 107 | money laundering 5.65 8 7 8 7 5 7 7.5 2 5 5 5 0 7 108 | money operation 3.31 4 2 3 5 5 5 2 2 4 3 5 1 2 109 | tiger jaguar 8.00 9 9 9 10 5 8 7.5 6 8 9 8.5 7 8 110 | tiger feline 8.00 9 7.5 9.5 8 5 8 8.5 8 8 9 8.5 7 8 111 | tiger carnivore 7.08 9 6 8 5 5 8 7 7 8.1 8 6 7 8 112 | tiger mammal 6.85 9 7 7.5 5 5 7 7 7 8 8 8.5 6 4 113 | tiger animal 7.00 8 7 7.5 5 5 6 6 7 7.5 9 10 5 8 114 | tiger organism 4.77 8 7 6 1 5 5 1 2 6 4 10 5 2 115 | tiger fauna 5.62 8 7 7.5 1 2 6 7 2 5.5 9 10 5 3 116 | tiger zoo 5.87 8 5.25 8 3 5 7 6 8 6 5 5 5 5 117 | psychology psychiatry 8.08 9 8.5 9.5 9 4 8 8 8 7 9 9 8 8 118 | psychology 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7 8 8 4 8 7.5 7 7 9 7 7 8 154 | jaguar car 7.27 9 9 8.5 8 4 8 7 7 8 9 4 5 8 155 | -------------------------------------------------------------------------------- /wordsim353/set2.csv: -------------------------------------------------------------------------------- 1 | Word 1,Word 2,Human (mean),1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 2 | energy,secretary,1.81,1,0,4,2,4,5,1,1,1,0,1,1,4,0,2,2 3 | secretary,senate,5.06,7,1,7,4,4,7,1,3,4,8,4,5,6,7,6,7 4 | energy,laboratory,5.09,7,1,7.5,4,6,7,4,6,1,2,4,3,7,9,6,7 5 | computer,laboratory,6.78,8,5,8,7,6,9,6,7,6,7.5,4,5,8,9,7,6 6 | weapon,secret,6.06,7,4,8,6,6,9,2,6,3,6,5,6,8,9,7,5 7 | FBI,fingerprint,6.94,8,6,8,5,5,9,7,7,6,6,6,8,9,7,6,8 8 | FBI,investigation,8.31,9,9,8.5,9,7,9,8,8,8,7.5,6,9,10,9,7,9 9 | investigation,effort,4.59,5,1,7.5,2,4,7,6,5,2,2,2,7,6,5,6,6 10 | Mars,water,2.94,2,1,3,2,1,8,0,4,2,6,1,1,3,0,5,8 11 | Mars,scientist,5.63,8,1,7,4,6,8,1,6,5,6,2,9,7,5,7,8 12 | news,report,8.16,9,6,8.5,8,7,9,7,8,7,8,7,9,10,9,9,9 13 | canyon,landscape,7.53,9,7.5,7,7,7,7,8,7,7,8,6,9,8,6,8,9 14 | image,surface,4.56,7,1,5,1,1,5,4,3,4,4,5,5,7,7,8,6 15 | discovery,space,6.34,8,2,7.5,9,5,7,4,7,5,6,5,7,8,8,7,6 16 | water,seepage,6.56,8,7,9,7,7,8,7,6,0,6,1,8,7,8,8,8 17 | sign,recess,2.38,4,1,2,4,5,4,0,4,3,0,1,0,0,0,6,4 18 | Wednesday,news,2.22,4,1,4,2,3,6,2,3,0.5,0,1,1,0,1,4,3 19 | mile,kilometer,8.66,9,9.5,9,8,9,8,9,9,8.5,7.5,8,8,10,8,9,9 20 | computer,news,4.47,5,1,7,6,5,5,1,4,6.5,4,2,5,3,7,6,4 21 | territory,surface,5.34,6,2,8.5,4,7,7,8,4,2,6,6,5,6,2,8,4 22 | atmosphere,landscape,3.69,7,0,2,1,8,7,1,5,2,0,2,5,6,1,7,5 23 | president,medal,3.00,5,2,1,3,6,6,1,7,2,0,1,3,2,1,4,4 24 | war,troops,8.13,8,8.5,9,9,8,8,8,8,6,7.5,8,8,9,8,9,8 25 | record,number,6.31,8,6,8,5,7,7,3,4,5,8,5,8,8,5,8,6 26 | skin,eye,6.22,7,9,7,3,6,6,7,7,6,7.5,5,6,8,2,8,5 27 | Japanese,American,6.50,7,6,8.5,6,6,4,8,7,7,7.5,5,8,9,1,8,6 28 | theater,history,3.91,5,6,6,4,5,3,0,3,6.5,6,1,5,1,1,7,3 29 | volunteer,motto,2.56,2,5,1,1,4,2,0,3,3,0,4,7,0,3,4,2 30 | prejudice,recognition,3.00,7,4,2,1,6,2,4,5,1,0,6,5,0,0,3,2 31 | decoration,valor,5.63,6,8,7,8,8,2,2,9,5,0,7,8,9,1,8,2 32 | century,year,7.59,8,9,8,9,7,6,8,8,7,7.5,7,9,8,5,9,6 33 | century,nation,3.16,5,0,7.5,5,4,4,0,2,2,4,2,2,2,0,8,3 34 | delay,racism,1.19,1,0,1,1,6,1,0,1,0,0,4,0,0,0,3,1 35 | delay,news,3.31,7,4,3,1,6,5,6,4,4,0,1,4,3,0,3,2 36 | minister,party,6.63,8,7.5,8,7,6,7,8,8,5,7.5,6,1,8,8,8,3 37 | peace,plan,4.75,5,2,7,6,7,4,3,5,4,4,5,3,7,2,9,3 38 | minority,peace,3.69,6,0,7,3,1,5,6,4,4,4,3,3,5,0,5,3 39 | attempt,peace,4.25,7,4,7,2,7,4,2,3,3,4,3,5,5,4,5,3 40 | government,crisis,6.56,8,5,8,5,7,7,5,6,5,6,7,8,7,9,7,5 41 | deployment,departure,4.25,7,0,2,6,7,5,6,4,2,2,5,6,2,0,8,6 42 | deployment,withdrawal,5.88,9,9,6,6,3,8,8,4,3,2,5,8,9,0,8,6 43 | energy,crisis,5.94,8,5,8,5,8,8,8,4,1,4,2,7,5,8,8,6 44 | announcement,news,7.56,8,7,8,8,8,9,8,6,6,8,8,8,6,8,9,6 45 | announcement,effort,2.75,5,6,2,2,1,5,4,2,2,2,2,0,3,0,5,3 46 | stroke,hospital,7.03,9,8,8,8,7,3,8,7,6,7.5,7,7,9,3,8,7 47 | disability,death,5.47,7,8,6.5,4,3,7,7,5,6,2,7,2,8,2,8,5 48 | victim,emergency,6.47,8,7,7.5,4,5,6,6,7,6,4,5,6,9,9,9,5 49 | treatment,recovery,7.91,8,8,8.5,9,9,8,9,8,6.5,7.5,7,7,10,5,9,7 50 | journal,association,4.97,8,2,7.5,7,1,5,4,6,3,6,7,3,7,1,8,4 51 | doctor,personnel,5.00,7,2,8,6,4,7,2,6,2,6,4,5,7,3,8,3 52 | doctor,liability,5.19,7,4,8,7,4,6,4,5,4,2,4,2,6,8,7,5 53 | liability,insurance,7.03,6,8.5,9,5,8,9,6,8,5,4,7,8,8,5,9,7 54 | school,center,3.44,6,1,4,1,5,2,4,3,3,4,5,1,3,3,7,3 55 | reason,hypertension,2.31,4,1,1,2,6,1,0,1,3,2,2,7,0,2,3,2 56 | reason,criterion,5.91,3,2,8,7,9,3,6,4,4.5,8,7,7,8,6,7,5 57 | hundred,percent,7.38,9,5,9,3,10,9,6,7,7,6,6,7,10,9,8,7 58 | Harvard,Yale,8.13,9,8,9,10,8,8,9,10,8.5,7.5,8,8,10,0,8,9 59 | hospital,infrastructure,4.63,5,2,1,5,6,5,4,7,3,4,5,5,5,3,7,7 60 | death,row,5.25,2,7,8,2,8,7,6,3,7,4,2,7,9,0,8,4 61 | death,inmate,5.03,4,5,7.5,1,5,4,7,3,6,2,6,6,3,8,8,5 62 | lawyer,evidence,6.69,7,6.5,8.5,7,8,6,8,8,7,3,5,8,10,0,9,6 63 | 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announcement,warning,6.00,7,7,5,7,8,4,4,8,5,7,6,8,3,8,7,2 112 | profit,warning,3.88,7,7,1,5,4,6,4,3,5,1,3,3,0,0,7,6 113 | profit,loss,7.63,8,9.5,9.5,10,8,8,8,9,6,4,8,8,10,0,9,7 114 | dollar,yen,7.78,8,9,9,10,7,5,8,8,7,7.5,8,8,10,3,9,8 115 | dollar,buck,9.22,9,10,9.5,10,9,8,9,10,9,8,10,10,8,9,10,9 116 | dollar,profit,7.38,8,6,9,9,9,7,7,8,8,6,7,5,6,7,8,8 117 | dollar,loss,6.09,8,6,8.5,2,5,7,7,8,4,6,5,5,5,7,8,6 118 | computer,software,8.50,9,8,9,8,9,8,8,9,8,9,8,8,10,9,9,7 119 | network,hardware,8.31,8,8.5,8.5,9,9,7,8,7,8,9,8,9,8,9,9,8 120 | phone,equipment,7.13,8,8.5,7.5,5,9,6,7,6,6,8,5,7,7,9,8,7 121 | equipment,maker,5.91,8,7,7,6,6,5,8,5,2,7.5,3,4,6,5,8,7 122 | luxury,car,6.47,7,6,8,6,7,7,5,5,3,7.5,6,6,7,7,8,8 123 | five,month,3.38,5,6,2,1,5,4,1,5,2,4,2,1,3,6,5,2 124 | report,gain,3.63,6,5,4,1,4,5,4,3,2,0,2,1,7,7,6,1 125 | investor,earning,7.13,8,7,8,8,7,7,8,7,3,8,7,6,8,7,8,7 126 | liquid,water,7.89,8,7.75,8.5,8,7,8,4,8,7,9,8,9,8,9,9,8 127 | baseball,season,5.97,8,3,8.5,7,8,8,4,6,5,8,3,6,7,2,7,5 128 | game,victory,7.03,8,8,7,7,5,8,6,7,6.5,8,7,5,9,8,7,6 129 | game,team,7.69,8,8.5,8.5,8,5,8,6,9,7,9,7,7,9,8,8,7 130 | marathon,sprint,7.47,7,9,7,8,6,8,7,8,6.5,9,8,8,5,9,8,6 131 | game,series,6.19,7,8,7.5,6,5,8,5,6,2,7.5,3,8,6,5,8,7 132 | game,defeat,6.97,8,8,7.5,7,6,8,6,7,6,8,7,5,9,6,7,6 133 | seven,series,3.56,5,6,2,2,5,4,4,5,3,4,4,1,0,1,7,4 134 | seafood,sea,7.47,9,8,7.5,8,9,9,7,7,7,9,6,6,5,7,8,7 135 | seafood,food,8.34,9,9.5,9,9,9,8,4,9,7,9,8,9,8,9,9,8 136 | seafood,lobster,8.70,9,9.75,8.5,10,9,9,6,10,7,9,9,9,8,9,9,8 137 | lobster,food,7.81,8,8,8,10,9,7,4,9,7,9,6,9,9,7,8,7 138 | lobster,wine,5.70,7,7.75,7.5,1,6,6,3,8,5.5,7.5,4,6,7,1,7,7 139 | food,preparation,6.22,6,5,6.5,5,9,6,3,7,6,8,5,6,6,7,8,6 140 | video,archive,6.34,7,6,7,5,9,7,4,7,4,7.5,5,7,5,9,8,4 141 | start,year,4.06,5,5.5,6.5,2,5,3,0,6,4,6,2,2,3,9,4,2 142 | start,match,4.47,5,2,6.5,1,9,3,3,8,1,2,3,5,5,9,6,3 143 | game,round,5.97,4,8,8,4,5,5,7,9,4,7.5,5,6,7,5,8,3 144 | boxing,round,7.61,6,8.25,7.5,7,8,7,8,9,4,8,7,8,10,9,9,6 145 | championship,tournament,8.36,9,8.75,9,9,9,8,7,10,7,8,8,8,10,9,8,6 146 | fighting,defeating,7.41,8,8,8,8,5,7,6,9,7,7.5,8,9,8,5,9,6 147 | line,insurance,2.69,5,2,2,1,6,3,3,4,1,2,2,2,0,0,9,1 148 | day,summer,3.94,7,7,2,1,4,3,1,7,3,4,4,4,6,1,5,4 149 | summer,drought,7.16,8,8,8,9,5,7,7,8,5,7.5,5,4,8,9,8,8 150 | summer,nature,5.63,5,6,4,7,9,5,6,7,4,6,6,3,3,6,7,6 151 | day,dawn,7.53,8,8.5,8,8,9,8,6,8,6,6,8,7,8,7,8,7 152 | nature,environment,8.31,9,6.5,8.5,9,9,9,7,9,8,8,8,8,10,9,8,7 153 | environment,ecology,8.81,9,8.5,8.5,9,9,9,8,10,8,9,9,9,10,7,9,9 154 | nature,man,6.25,5,6,8,5,9,5,5,7,3,8,5,6,8,5,8,7 155 | man,woman,8.30,8,9.75,9,10,9,9,8,9,7.5,7.5,9,9,10,1,9,8 156 | man,governor,5.25,7,4.5,5,1,6,4,3,7,2,7.5,3,7,7,8,7,5 157 | murder,manslaughter,8.53,8,9.9,9.5,10,7,9,9,10,6,4,8,9,9,9,10,9 158 | soap,opera,7.94,8,4,8.5,7,9,9,8,9,8,7.5,7,8,9,9,7,9 159 | opera,performance,6.88,8,2,7.5,5,9,5,7,7,8,7.5,6,9,7,9,7,6 160 | life,lesson,5.94,7,5,7.5,3,9,8,4,6,5,7.5,4,5,2,9,7,6 161 | focus,life,4.06,5,0,7.5,1,7,6,0,3,4,7.5,3,2,2,7,5,5 162 | production,crew,6.25,8,4,8,4,8,7,5,7,3,8,4,7,9,9,6,3 163 | television,film,7.72,8,5,8.5,8,9,8,8,9,5,8,7,8,9,9,8,6 164 | lover,quarrel,6.19,7,2,8.5,3,7,7,6,9,5,7.5,4,6,8,7,7,5 165 | viewer,serial,2.97,3,0.5,1,1,4,3,0,6,2,2,2,7,7,3,4,2 166 | possibility,girl,1.94,3,0,0,1,4,2,0,2,2,4,3,1,0,3,5,1 167 | population,development,3.75,5,1,3,2,7,5,2,7,2,6,4,1,4,1,5,5 168 | morality,importance,3.31,7,0,1,1,6,4,0,6,1,6,3,3,3,4,4,4 169 | morality,marriage,3.69,6,5,2,1,5,4,1,3,3,6,3,5,4,1,4,6 170 | Mexico,Brazil,7.44,8,8.5,8,6,7,7,8,9,7,7.5,7,8,10,2,8,8 171 | gender,equality,6.41,8,6,5,4,4,8,5,8,6,7.5,2,8,8,7,7,9 172 | change,attitude,5.44,8,5,6,3,4,7,4,7,7,6,4,6,5,0,7,8 173 | family,planning,6.25,7,5,7,3,7,8,4,6,7,8,7,6,8,1,8,8 174 | opera,industry,2.63,7,0,1,1,7,2,3,3,2,2,1,2,3,1,4,3 175 | sugar,approach,0.88,3,0,0,1,5,1,0,1,0,0,1,0,0,0,1,1 176 | practice,institution,3.19,4,1,1,1,6,2,2,2,4,3,6,6,5,0,5,3 177 | ministry,culture,4.69,4,1,6,4,7,6,1,4,5,6,5,7,6,7,3,3 178 | problem,challenge,6.75,7,7.5,7.5,8,7,7,1,10,5,6,6,8,8,8,7,5 179 | size,prominence,5.31,7,8.5,6,7,6,4,2,8,3.5,2,6,5,6,1,7,6 180 | country,citizen,7.31,8,7,7,9,8,7,7,7,5,8,7,8,9,6,8,6 181 | planet,people,5.75,5,0,6,7,8,5,6,5,5,9,7,6,4,7,7,5 182 | development,issue,3.97,5,1,6,1,5,3,1,5,3,7.5,3,7,3,2,5,6 183 | experience,music,3.47,6,1,7,1,5,3,1,1,1,7.5,3,8,3,1,5,2 184 | music,project,3.63,5,0,6,1,5,3,4,2,3,6,5,2,7,2,4,3 185 | glass,metal,5.56,7,7,8,4,6,5,4,7,6,4,7,7,6,0,5,6 186 | aluminum,metal,7.83,9,8.75,9,9,7,7,6,8,6,7.5,8,9,8,8,8,7 187 | chance,credibility,3.88,8,3,1,3,6,3,3,4,3,6,3,8,1,1,4,5 188 | exhibit,memorabilia,5.31,7,6,9,7,7,3,2,7,3,6,7,7,5,2,1,6 189 | concert,virtuoso,6.81,8,6,7.5,9,6,7,7,8,2,7.5,7,7,8,3,8,8 190 | rock,jazz,7.59,8,9,9,5,8,7,8,9,7,7.5,8,8,9,1,9,9 191 | museum,theater,7.19,8,7.5,8.5,6,8,8,8,9,7,6,8,8,7,1,8,7 192 | observation,architecture,4.38,7,3,3,4,6,3,6,5,3,4,7,7,3,1,2,6 193 | space,world,6.53,7,6,8.5,3,9,6,7,9,5,6,8,8,5,3,8,6 194 | preservation,world,6.19,7,8,7,6,7,7,2,8,4,6,6,8,8,4,6,5 195 | admission,ticket,7.69,8,8,9,9,9,8,7,9,6,6,6,9,9,5,8,7 196 | shower,thunderstorm,6.31,8,9,8,6,7,8,2,7,6,4,5,9,8,2,8,4 197 | shower,flood,6.03,8,7,8.5,6,7,8,2,7,6,6,7,8,8,0,4,4 198 | weather,forecast,8.34,8,7.5,9,9,9,9,7,9,7,8,8,9,10,7,9,8 199 | disaster,area,6.25,7,8,9,3,9,8,3,5,6,6,5,8,9,1,5,8 200 | governor,office,6.34,8,5,7.5,3,7,8,1,6,5,6,6,8,7,8,8,8 201 | architecture,century,3.78,6,0,7.5,1,6,8,1,3,1,6,5,7,3,2,2,2 202 | -------------------------------------------------------------------------------- /wordsim353/set2.tab: -------------------------------------------------------------------------------- 1 | Word 1 Word 2 Human (mean) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 2 | energy secretary 1.81 1 0 4 2 4 5 1 1 1 0 1 1 4 0 2 2 3 | secretary senate 5.06 7 1 7 4 4 7 1 3 4 8 4 5 6 7 6 7 4 | energy laboratory 5.09 7 1 7.5 4 6 7 4 6 1 2 4 3 7 9 6 7 5 | computer laboratory 6.78 8 5 8 7 6 9 6 7 6 7.5 4 5 8 9 7 6 6 | weapon secret 6.06 7 4 8 6 6 9 2 6 3 6 5 6 8 9 7 5 7 | FBI fingerprint 6.94 8 6 8 5 5 9 7 7 6 6 6 8 9 7 6 8 8 | FBI investigation 8.31 9 9 8.5 9 7 9 8 8 8 7.5 6 9 10 9 7 9 9 | investigation effort 4.59 5 1 7.5 2 4 7 6 5 2 2 2 7 6 5 6 6 10 | Mars water 2.94 2 1 3 2 1 8 0 4 2 6 1 1 3 0 5 8 11 | Mars scientist 5.63 8 1 7 4 6 8 1 6 5 6 2 9 7 5 7 8 12 | news report 8.16 9 6 8.5 8 7 9 7 8 7 8 7 9 10 9 9 9 13 | canyon landscape 7.53 9 7.5 7 7 7 7 8 7 7 8 6 9 8 6 8 9 14 | image surface 4.56 7 1 5 1 1 5 4 3 4 4 5 5 7 7 8 6 15 | discovery space 6.34 8 2 7.5 9 5 7 4 7 5 6 5 7 8 8 7 6 16 | water seepage 6.56 8 7 9 7 7 8 7 6 0 6 1 8 7 8 8 8 17 | sign recess 2.38 4 1 2 4 5 4 0 4 3 0 1 0 0 0 6 4 18 | Wednesday news 2.22 4 1 4 2 3 6 2 3 0.5 0 1 1 0 1 4 3 19 | mile kilometer 8.66 9 9.5 9 8 9 8 9 9 8.5 7.5 8 8 10 8 9 9 20 | computer news 4.47 5 1 7 6 5 5 1 4 6.5 4 2 5 3 7 6 4 21 | territory surface 5.34 6 2 8.5 4 7 7 8 4 2 6 6 5 6 2 8 4 22 | atmosphere landscape 3.69 7 0 2 1 8 7 1 5 2 0 2 5 6 1 7 5 23 | president medal 3.00 5 2 1 3 6 6 1 7 2 0 1 3 2 1 4 4 24 | war troops 8.13 8 8.5 9 9 8 8 8 8 6 7.5 8 8 9 8 9 8 25 | record number 6.31 8 6 8 5 7 7 3 4 5 8 5 8 8 5 8 6 26 | skin eye 6.22 7 9 7 3 6 6 7 7 6 7.5 5 6 8 2 8 5 27 | Japanese American 6.50 7 6 8.5 6 6 4 8 7 7 7.5 5 8 9 1 8 6 28 | theater history 3.91 5 6 6 4 5 3 0 3 6.5 6 1 5 1 1 7 3 29 | volunteer motto 2.56 2 5 1 1 4 2 0 3 3 0 4 7 0 3 4 2 30 | prejudice recognition 3.00 7 4 2 1 6 2 4 5 1 0 6 5 0 0 3 2 31 | decoration valor 5.63 6 8 7 8 8 2 2 9 5 0 7 8 9 1 8 2 32 | century year 7.59 8 9 8 9 7 6 8 8 7 7.5 7 9 8 5 9 6 33 | century nation 3.16 5 0 7.5 5 4 4 0 2 2 4 2 2 2 0 8 3 34 | delay racism 1.19 1 0 1 1 6 1 0 1 0 0 4 0 0 0 3 1 35 | delay news 3.31 7 4 3 1 6 5 6 4 4 0 1 4 3 0 3 2 36 | minister party 6.63 8 7.5 8 7 6 7 8 8 5 7.5 6 1 8 8 8 3 37 | peace plan 4.75 5 2 7 6 7 4 3 5 4 4 5 3 7 2 9 3 38 | minority peace 3.69 6 0 7 3 1 5 6 4 4 4 3 3 5 0 5 3 39 | attempt peace 4.25 7 4 7 2 7 4 2 3 3 4 3 5 5 4 5 3 40 | government crisis 6.56 8 5 8 5 7 7 5 6 5 6 7 8 7 9 7 5 41 | deployment departure 4.25 7 0 2 6 7 5 6 4 2 2 5 6 2 0 8 6 42 | deployment withdrawal 5.88 9 9 6 6 3 8 8 4 3 2 5 8 9 0 8 6 43 | energy crisis 5.94 8 5 8 5 8 8 8 4 1 4 2 7 5 8 8 6 44 | announcement news 7.56 8 7 8 8 8 9 8 6 6 8 8 8 6 8 9 6 45 | announcement effort 2.75 5 6 2 2 1 5 4 2 2 2 2 0 3 0 5 3 46 | stroke hospital 7.03 9 8 8 8 7 3 8 7 6 7.5 7 7 9 3 8 7 47 | disability death 5.47 7 8 6.5 4 3 7 7 5 6 2 7 2 8 2 8 5 48 | victim emergency 6.47 8 7 7.5 4 5 6 6 7 6 4 5 6 9 9 9 5 49 | treatment recovery 7.91 8 8 8.5 9 9 8 9 8 6.5 7.5 7 7 10 5 9 7 50 | journal association 4.97 8 2 7.5 7 1 5 4 6 3 6 7 3 7 1 8 4 51 | doctor personnel 5.00 7 2 8 6 4 7 2 6 2 6 4 5 7 3 8 3 52 | doctor liability 5.19 7 4 8 7 4 6 4 5 4 2 4 2 6 8 7 5 53 | liability insurance 7.03 6 8.5 9 5 8 9 6 8 5 4 7 8 8 5 9 7 54 | school center 3.44 6 1 4 1 5 2 4 3 3 4 5 1 3 3 7 3 55 | reason hypertension 2.31 4 1 1 2 6 1 0 1 3 2 2 7 0 2 3 2 56 | reason criterion 5.91 3 2 8 7 9 3 6 4 4.5 8 7 7 8 6 7 5 57 | hundred percent 7.38 9 5 9 3 10 9 6 7 7 6 6 7 10 9 8 7 58 | Harvard Yale 8.13 9 8 9 10 8 8 9 10 8.5 7.5 8 8 10 0 8 9 59 | hospital infrastructure 4.63 5 2 1 5 6 5 4 7 3 4 5 5 5 3 7 7 60 | death row 5.25 2 7 8 2 8 7 6 3 7 4 2 7 9 0 8 4 61 | death inmate 5.03 4 5 7.5 1 5 4 7 3 6 2 6 6 3 8 8 5 62 | lawyer evidence 6.69 7 6.5 8.5 7 8 6 8 8 7 3 5 8 10 0 9 6 63 | life death 7.88 9 9.5 9.5 5 10 8 8 8 6.5 7.5 8 9 10 0 9 9 64 | life term 4.50 2 8 2 1 8 7 6 3 1 4 2 8 3 3 8 6 65 | word similarity 4.75 6 1 8 2 10 7 6 2 1 4 2 5 0 9 7 6 66 | board recommendation 4.47 6 4 2 1 7 8 3 4 1 7.5 2 7 7 0 7 5 67 | governor interview 3.25 4 0 4 1 7 6 0 5 0 2 3 5 3 3 4 5 68 | OPEC country 5.63 7 4 8 4 0 4 8 6 5 8 4 6 7 8 6 5 69 | peace atmosphere 3.69 6 5 5 1 0 6 3 5 2 6 1 3 3 0 7 6 70 | peace insurance 2.94 6 4 1 1 7 4 0 3 2 6 5 1 0 0 3 4 71 | territory kilometer 5.28 6 6 8 1 5 8 7 6 4 7.5 5 3 3 2 8 5 72 | travel activity 5.00 7 5 6.5 2 5 6 6 6 5 7.5 3 2 4 2 8 5 73 | competition price 6.44 7 8 7.5 5 6 7 8 4 6 7.5 5 6 9 5 9 3 74 | consumer confidence 4.13 7 4 2 3 3 3 1 2 2 6 2 7 9 4 8 3 75 | consumer energy 4.75 5 3 8 2 6 6 0 4 0 4 7 6 6 9 8 2 76 | problem airport 2.38 2 2 1 0 5 4 0 3 0 4 1 2 0 7 5 2 77 | car flight 4.94 6 3 7 5 6 6 4 7 4 2 7 5 8 0 5 4 78 | credit card 8.06 8 6 9 8 9 8 8 9 7 8 5 8 10 9 9 8 79 | credit information 5.31 7 5 2 3 7 4 1 5 7 1 2 8 10 9 8 6 80 | hotel reservation 8.03 8 7 9 7 8 8 8 8 7 7.5 7 8 10 9 9 8 81 | grocery money 5.94 8 5 7.5 2 7 7 7 5 6.5 6 6 8 6 2 5 7 82 | registration arrangement 6.00 8 8 7 7 8 4 1 4 7 6 6 6 8 3 8 5 83 | arrangement accommodation 5.41 5 6 7 6 4 4 4 6 3 7.5 5 5 7 6 7 4 84 | month hotel 1.81 4 0 1 1 3 6 0 2 1 1 2 0 3 0 3 2 85 | type kind 8.97 9 9.5 9.5 10 8 9 9 10 8.5 9 9 9 9 9 9 7 86 | arrival hotel 6.00 7 8 6.5 1 6 9 7 5 6 7.5 4 6 7 4 6 6 87 | bed closet 6.72 8 7.5 8 5 7 8 7 8 7 6 7 5 9 1 8 6 88 | closet clothes 8.00 8 7 9 10 8 9 8 9 9 8 7 8 9 3 9 7 89 | situation conclusion 4.81 8 4 6 4 6 3 7 6 2 6 6 7 4 0 6 2 90 | situation isolation 3.88 8 3 1 2 6 3 0 3 2 6 6 7 3 0 8 4 91 | impartiality interest 5.16 7 9.5 8 2 4 3 0 7 6 3 7 6 9 0 8 3 92 | direction combination 2.25 2 0 1 1 7 2 0 2 2 2 4 3 0 1 6 3 93 | street place 6.44 7 7 6 7 5 7 5 7 6 4 7 8 4 7 9 7 94 | street avenue 8.88 9 9 8.5 9 9 9 7 10 8.5 9 7 9 10 9 10 9 95 | street block 6.88 5 7 8.5 7 4 8 7 9 8.5 9 6 9 4 0 9 9 96 | street children 4.94 6 6 6 2 5 7 2 5 4 6 3 5 6 5 5 6 97 | listing proximity 2.56 3 0 1 1 5 4 0 3 1 2 2 4 3 1 7 4 98 | listing category 6.38 2 3 7 9 7 6 7 7 4 8 7 8 10 3 8 6 99 | cell phone 7.81 8 6 8 9 9 8 8 8 8 8 3 9 8 9 8 8 100 | production hike 1.75 2 2 1 1 6 3 0 1 1 0 2 3 0 0 4 2 101 | benchmark index 4.25 5 5 2 2 7 4 5 7 3 1 7 2 6 4 5 3 102 | media trading 3.88 6 2 5 1 7 6 3 4 2 2 6 2 5 0 8 3 103 | media gain 2.88 5 0 2 1 7 4 2 2 3 2 5 1 3 0 7 2 104 | dividend payment 7.63 6 9 7 4 9 8 8 8 7 8 7 8 8 9 9 7 105 | dividend calculation 6.48 7 8.75 6.5 1 9 7 6 7 6.5 8 3 6 7 8 8 5 106 | calculation computation 8.44 9 9.5 9.5 8 8 9 5 10 9 8 8 9 7 9 9 8 107 | currency market 7.50 8 5 7.5 5 9 8 7 8 7 7.5 6 8 8 9 9 8 108 | OPEC oil 8.59 8 8 9 10 10 8 8 8 8 7.5 7 9 10 9 9 9 109 | oil stock 6.34 6 5 8 6 7 6 2 6 8 7.5 6 6 7 8 7 6 110 | announcement production 3.38 5 0 3 2 6 5 1 4 2 2 3 6 3 5 6 1 111 | announcement warning 6.00 7 7 5 7 8 4 4 8 5 7 6 8 3 8 7 2 112 | profit warning 3.88 7 7 1 5 4 6 4 3 5 1 3 3 0 0 7 6 113 | profit loss 7.63 8 9.5 9.5 10 8 8 8 9 6 4 8 8 10 0 9 7 114 | dollar yen 7.78 8 9 9 10 7 5 8 8 7 7.5 8 8 10 3 9 8 115 | dollar buck 9.22 9 10 9.5 10 9 8 9 10 9 8 10 10 8 9 10 9 116 | dollar profit 7.38 8 6 9 9 9 7 7 8 8 6 7 5 6 7 8 8 117 | dollar loss 6.09 8 6 8.5 2 5 7 7 8 4 6 5 5 5 7 8 6 118 | computer software 8.50 9 8 9 8 9 8 8 9 8 9 8 8 10 9 9 7 119 | network hardware 8.31 8 8.5 8.5 9 9 7 8 7 8 9 8 9 8 9 9 8 120 | phone equipment 7.13 8 8.5 7.5 5 9 6 7 6 6 8 5 7 7 9 8 7 121 | equipment maker 5.91 8 7 7 6 6 5 8 5 2 7.5 3 4 6 5 8 7 122 | luxury car 6.47 7 6 8 6 7 7 5 5 3 7.5 6 6 7 7 8 8 123 | five month 3.38 5 6 2 1 5 4 1 5 2 4 2 1 3 6 5 2 124 | report gain 3.63 6 5 4 1 4 5 4 3 2 0 2 1 7 7 6 1 125 | investor earning 7.13 8 7 8 8 7 7 8 7 3 8 7 6 8 7 8 7 126 | liquid water 7.89 8 7.75 8.5 8 7 8 4 8 7 9 8 9 8 9 9 8 127 | baseball season 5.97 8 3 8.5 7 8 8 4 6 5 8 3 6 7 2 7 5 128 | game victory 7.03 8 8 7 7 5 8 6 7 6.5 8 7 5 9 8 7 6 129 | game team 7.69 8 8.5 8.5 8 5 8 6 9 7 9 7 7 9 8 8 7 130 | marathon sprint 7.47 7 9 7 8 6 8 7 8 6.5 9 8 8 5 9 8 6 131 | game series 6.19 7 8 7.5 6 5 8 5 6 2 7.5 3 8 6 5 8 7 132 | game defeat 6.97 8 8 7.5 7 6 8 6 7 6 8 7 5 9 6 7 6 133 | seven series 3.56 5 6 2 2 5 4 4 5 3 4 4 1 0 1 7 4 134 | seafood sea 7.47 9 8 7.5 8 9 9 7 7 7 9 6 6 5 7 8 7 135 | seafood food 8.34 9 9.5 9 9 9 8 4 9 7 9 8 9 8 9 9 8 136 | seafood lobster 8.70 9 9.75 8.5 10 9 9 6 10 7 9 9 9 8 9 9 8 137 | lobster food 7.81 8 8 8 10 9 7 4 9 7 9 6 9 9 7 8 7 138 | lobster wine 5.70 7 7.75 7.5 1 6 6 3 8 5.5 7.5 4 6 7 1 7 7 139 | food preparation 6.22 6 5 6.5 5 9 6 3 7 6 8 5 6 6 7 8 6 140 | video archive 6.34 7 6 7 5 9 7 4 7 4 7.5 5 7 5 9 8 4 141 | start year 4.06 5 5.5 6.5 2 5 3 0 6 4 6 2 2 3 9 4 2 142 | start match 4.47 5 2 6.5 1 9 3 3 8 1 2 3 5 5 9 6 3 143 | game round 5.97 4 8 8 4 5 5 7 9 4 7.5 5 6 7 5 8 3 144 | boxing round 7.61 6 8.25 7.5 7 8 7 8 9 4 8 7 8 10 9 9 6 145 | championship tournament 8.36 9 8.75 9 9 9 8 7 10 7 8 8 8 10 9 8 6 146 | fighting defeating 7.41 8 8 8 8 5 7 6 9 7 7.5 8 9 8 5 9 6 147 | line insurance 2.69 5 2 2 1 6 3 3 4 1 2 2 2 0 0 9 1 148 | day summer 3.94 7 7 2 1 4 3 1 7 3 4 4 4 6 1 5 4 149 | summer drought 7.16 8 8 8 9 5 7 7 8 5 7.5 5 4 8 9 8 8 150 | summer nature 5.63 5 6 4 7 9 5 6 7 4 6 6 3 3 6 7 6 151 | day dawn 7.53 8 8.5 8 8 9 8 6 8 6 6 8 7 8 7 8 7 152 | nature environment 8.31 9 6.5 8.5 9 9 9 7 9 8 8 8 8 10 9 8 7 153 | environment ecology 8.81 9 8.5 8.5 9 9 9 8 10 8 9 9 9 10 7 9 9 154 | nature man 6.25 5 6 8 5 9 5 5 7 3 8 5 6 8 5 8 7 155 | man woman 8.30 8 9.75 9 10 9 9 8 9 7.5 7.5 9 9 10 1 9 8 156 | man governor 5.25 7 4.5 5 1 6 4 3 7 2 7.5 3 7 7 8 7 5 157 | murder manslaughter 8.53 8 9.9 9.5 10 7 9 9 10 6 4 8 9 9 9 10 9 158 | soap opera 7.94 8 4 8.5 7 9 9 8 9 8 7.5 7 8 9 9 7 9 159 | opera performance 6.88 8 2 7.5 5 9 5 7 7 8 7.5 6 9 7 9 7 6 160 | life lesson 5.94 7 5 7.5 3 9 8 4 6 5 7.5 4 5 2 9 7 6 161 | focus life 4.06 5 0 7.5 1 7 6 0 3 4 7.5 3 2 2 7 5 5 162 | production crew 6.25 8 4 8 4 8 7 5 7 3 8 4 7 9 9 6 3 163 | television film 7.72 8 5 8.5 8 9 8 8 9 5 8 7 8 9 9 8 6 164 | lover quarrel 6.19 7 2 8.5 3 7 7 6 9 5 7.5 4 6 8 7 7 5 165 | viewer serial 2.97 3 0.5 1 1 4 3 0 6 2 2 2 7 7 3 4 2 166 | possibility girl 1.94 3 0 0 1 4 2 0 2 2 4 3 1 0 3 5 1 167 | population development 3.75 5 1 3 2 7 5 2 7 2 6 4 1 4 1 5 5 168 | morality importance 3.31 7 0 1 1 6 4 0 6 1 6 3 3 3 4 4 4 169 | morality marriage 3.69 6 5 2 1 5 4 1 3 3 6 3 5 4 1 4 6 170 | Mexico Brazil 7.44 8 8.5 8 6 7 7 8 9 7 7.5 7 8 10 2 8 8 171 | gender equality 6.41 8 6 5 4 4 8 5 8 6 7.5 2 8 8 7 7 9 172 | change attitude 5.44 8 5 6 3 4 7 4 7 7 6 4 6 5 0 7 8 173 | family planning 6.25 7 5 7 3 7 8 4 6 7 8 7 6 8 1 8 8 174 | opera industry 2.63 7 0 1 1 7 2 3 3 2 2 1 2 3 1 4 3 175 | sugar approach 0.88 3 0 0 1 5 1 0 1 0 0 1 0 0 0 1 1 176 | practice institution 3.19 4 1 1 1 6 2 2 2 4 3 6 6 5 0 5 3 177 | ministry culture 4.69 4 1 6 4 7 6 1 4 5 6 5 7 6 7 3 3 178 | problem challenge 6.75 7 7.5 7.5 8 7 7 1 10 5 6 6 8 8 8 7 5 179 | size prominence 5.31 7 8.5 6 7 6 4 2 8 3.5 2 6 5 6 1 7 6 180 | country citizen 7.31 8 7 7 9 8 7 7 7 5 8 7 8 9 6 8 6 181 | planet people 5.75 5 0 6 7 8 5 6 5 5 9 7 6 4 7 7 5 182 | development issue 3.97 5 1 6 1 5 3 1 5 3 7.5 3 7 3 2 5 6 183 | experience music 3.47 6 1 7 1 5 3 1 1 1 7.5 3 8 3 1 5 2 184 | music project 3.63 5 0 6 1 5 3 4 2 3 6 5 2 7 2 4 3 185 | glass metal 5.56 7 7 8 4 6 5 4 7 6 4 7 7 6 0 5 6 186 | aluminum metal 7.83 9 8.75 9 9 7 7 6 8 6 7.5 8 9 8 8 8 7 187 | chance credibility 3.88 8 3 1 3 6 3 3 4 3 6 3 8 1 1 4 5 188 | exhibit memorabilia 5.31 7 6 9 7 7 3 2 7 3 6 7 7 5 2 1 6 189 | concert virtuoso 6.81 8 6 7.5 9 6 7 7 8 2 7.5 7 7 8 3 8 8 190 | rock jazz 7.59 8 9 9 5 8 7 8 9 7 7.5 8 8 9 1 9 9 191 | museum theater 7.19 8 7.5 8.5 6 8 8 8 9 7 6 8 8 7 1 8 7 192 | observation architecture 4.38 7 3 3 4 6 3 6 5 3 4 7 7 3 1 2 6 193 | space world 6.53 7 6 8.5 3 9 6 7 9 5 6 8 8 5 3 8 6 194 | preservation world 6.19 7 8 7 6 7 7 2 8 4 6 6 8 8 4 6 5 195 | admission ticket 7.69 8 8 9 9 9 8 7 9 6 6 6 9 9 5 8 7 196 | shower thunderstorm 6.31 8 9 8 6 7 8 2 7 6 4 5 9 8 2 8 4 197 | shower flood 6.03 8 7 8.5 6 7 8 2 7 6 6 7 8 8 0 4 4 198 | weather forecast 8.34 8 7.5 9 9 9 9 7 9 7 8 8 9 10 7 9 8 199 | disaster area 6.25 7 8 9 3 9 8 3 5 6 6 5 8 9 1 5 8 200 | governor office 6.34 8 5 7.5 3 7 8 1 6 5 6 6 8 7 8 8 8 201 | architecture century 3.78 6 0 7.5 1 6 8 1 3 1 6 5 7 3 2 2 2 202 | --------------------------------------------------------------------------------