├── .gitignore
├── README.md
├── common.py
├── dataset
    ├── adjective-pairs.test
    ├── adjective-pairs.train
    ├── adjective-pairs.val
    ├── noun-pairs.test
    ├── noun-pairs.train
    ├── noun-pairs.val
    ├── verb-pairs.test
    ├── verb-pairs.train
    └── verb-pairs.val
├── preprocess
    ├── create_dataset.py
    ├── create_resources.py
    └── parse_corpus.py
└── train_ant_syn_net.py


/.gitignore:
--------------------------------------------------------------------------------
1 | 
2 | .project
3 | 
4 | .pydevproject
5 | 


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/README.md:
--------------------------------------------------------------------------------
 1 | ## Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network
 2 | Kim Anh Nguyen, nguyenkh@ims.uni-stuttgart.de
 3 | 
 4 | Code for paper [Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network](http://www.ims.uni-stuttgart.de/institut/mitarbeiter/anhnk/papers/eacl2017/ant_syn_net.pdf) (EACL 2017).
 5 | 
 6 | ### Prerequisite
 7 | 1. [NetworkX](https://networkx.github.io): for creating the tree
 8 | 2. [spaCy](https://spacy.io): for parsing
 9 | 3. Theano
10 | 
11 | ### Preprocessing
12 | - Step 1: parse the corpus to create the patterns (```preprocess/parse_corpus.py```)
13 | - Step 2: create the resources which is used to train the model (```preprocess/create_resources.py```)
14 | 
15 | ### Training models
16 | 
17 | ```python train_ant_syn_net.py -corpus <corpus_prefix> -data <dataset_prefix> -emb <embeddings_file> -model <model_name> -iter <iteration>```
18 | 
19 | in which:
20 | - ```<corpus_prefix>```: the prefix of corpus
21 | - ```<dataset_prefix>```: the prefix of dataset
22 | - ```<embeddings_file>```: the embeddings file
23 | - ```<model_name>```: 1 for training the combined model or 0 for training the pattern-based model
24 | - ```<iteration>```: the number of epoch
25 | 
26 | ### Reference
27 | ```
28 | @InProceedings{nguyen:2017:ant_syn_net
29 |   author    = {Nguyen, Kim Anh and Schulte im Walde, Sabine and Vu, Ngoc Thang},
30 |   title     = {Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network},
31 |   booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL)},
32 |   year      = {2017},
33 |   address = {Valencia, Spain},
34 | }
35 | ```
36 | 


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/common.py:
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  1 | from itertools import count
  2 | from collections import defaultdict, OrderedDict
  3 | import random
  4 | import cPickle
  5 | import numpy
  6 | from numpy import fromstring, dtype
  7 | import theano
  8 | 
  9 | class Resources():
 10 |     """
 11 |     Holds the resources
 12 |     """
 13 |     def __init__(self, resource_prefix):
 14 |         """
 15 |         Initialize the resources
 16 |         """
 17 |         self.term_to_id = cPickle.load(open(resource_prefix + '_term_to_id.p', 'rb'))
 18 |         self.id_to_term = cPickle.load(open(resource_prefix + '_id_to_term.p', 'rb'))
 19 |         self.path_to_id = cPickle.load(open(resource_prefix + '_path_to_id.p', 'rb'))
 20 |         self.id_to_path = cPickle.load(open(resource_prefix + '_id_to_path.p', 'rb'))
 21 |         self.pattern = cPickle.load(open(resource_prefix + '_patterns.p', 'rb'))
 22 | 
 23 |     def get_term_by_id(self, id):
 24 |         return self.id_to_term[str(id)]
 25 | 
 26 |     def get_path_by_id(self, id):
 27 |         return self.id_to_path[str(id)]
 28 | 
 29 |     def get_id_by_term(self, term):
 30 |         return int(self.term_to_id[term]) if self.term_to_id.has_key(term) else -1
 31 | 
 32 |     def get_id_by_path(self, path):
 33 |         return int(self.path_to_id[path]) if self.path_to_id.has_key(path) else -1
 34 | 
 35 |     def get_patterns(self, x, y):
 36 |         """
 37 |         Returns the relations from x to y
 38 |         """
 39 |         pattern_dict = {}
 40 |         key = str(x) + '###' + str(y)
 41 |         path_str = self.pattern[key] if self.pattern.has_key(key) else ''
 42 | 
 43 |         if len(path_str) > 0:
 44 |             paths = [tuple(map(int, p.split(':'))) for p in path_str.split(',')]
 45 |             pattern_dict = { path : count for (path, count) in paths }
 46 | 
 47 |         return pattern_dict
 48 | 
 49 | def preprocess_instance(instance, maxlen=12):
 50 |     paths = instance.keys()
 51 |     n_samples = len(paths)
 52 | 
 53 |     l = numpy.zeros((maxlen, n_samples)).astype('int64')
 54 |     p = numpy.zeros((maxlen, n_samples)).astype('int64')
 55 |     g = numpy.zeros((maxlen, n_samples)).astype('int64')
 56 |     d = numpy.zeros((maxlen, n_samples)).astype('int64')
 57 |     mask = numpy.zeros((maxlen, n_samples)).astype(theano.config.floatX)
 58 |     c = numpy.zeros((n_samples, n_samples)).astype('int64')
 59 | 
 60 |     for idx, path in enumerate(paths):
 61 |         c[idx,idx] = instance[path]
 62 |         for i,node in enumerate(path):
 63 |             l[i,idx] = node[0]
 64 |             p[i,idx] = node[1]
 65 |             g[i,idx] = node[2]
 66 |             d[i,idx] = node[3]
 67 |             mask[i,idx] = 1.
 68 | 
 69 |     return l, p, g, d, mask, c   
 70 | 
 71 | def load_data(corpus_prefix, dataset_prefix, embeddings_file=None):
 72 |     '''
 73 |     Loads the resources
 74 |     '''
 75 |     print "Loading dataset..."
 76 |     train_set = load_dataset(dataset_prefix + '.train')
 77 |     test_set = load_dataset(dataset_prefix + '.test')
 78 |     valid_set = load_dataset(dataset_prefix + '.val')
 79 |     y_train = [int(train_set[key]) for key in train_set.keys()]
 80 |     y_test = [int(test_set[key]) for key in test_set.keys()]
 81 |     y_valid = [int(valid_set[key]) for key in valid_set.keys()]
 82 |     
 83 |     dataset_keys = train_set.keys() + test_set.keys() + valid_set.keys()
 84 |     
 85 |     vocab = OrderedDict()
 86 |     for kk in dataset_keys:
 87 |         vocab[kk[0]]
 88 |         vocab[kk[1]]
 89 |         
 90 |     print 'Initializing word embeddings...' 
 91 |       
 92 |     if embeddings_file is not None:
 93 |         vecs, words = load_embeddings(embeddings_file, vocab)    
 94 |         key_pairs, patterns, lemma, pos, dep, dist = load_patterns(corpus_prefix, dataset_keys, words)     
 95 |     else:
 96 |         key_pairs, patterns, lemma, pos, dep, dist = load_patterns(corpus_prefix, dataset_keys) 
 97 |         vecs = None
 98 |     
 99 |     print 'Number of lemmas: %d, POS tags: %d, dependency labels: %d, distance labels: %d'\
100 |           %(len(lemma), len(pos), len(dep), len(dist))
101 | 
102 |     X_train = patterns[:len(train_set)]
103 |     X_test = patterns[len(train_set):len(train_set)+len(test_set)]
104 |     X_valid = patterns[len(train_set)+len(test_set):]
105 |     
106 |     train_key_pairs = key_pairs[:len(train_set)]
107 |     test_key_pairs = key_pairs[len(train_set):len(train_set)+len(test_set)]
108 |     valid_key_pairs = key_pairs[len(train_set)+len(test_set):]
109 | 
110 |     train = (X_train, y_train)
111 |     test = (X_test, y_test)
112 |     valid = (X_valid, y_valid)
113 |     keys = (train_key_pairs, test_key_pairs, valid_key_pairs)
114 |         
115 |     return vecs, train, valid, test, keys, lemma, pos, dep, dist
116 | 
117 | def load_patterns(corpus_prefix, dataset_keys, words=None):
118 |     """
119 |     Loads patterns from the database
120 |     """
121 | 
122 |     # Define the dictionaries
123 |     if words is None:     
124 |         lemma = defaultdict(count(0).next)
125 |         pre_trained_embs = False
126 |         lemma['#UNKNOWN#']
127 |     else:
128 |         lemma = words
129 |         pre_trained_embs = True
130 |         
131 |     pos = defaultdict(count(0).next)
132 |     dep = defaultdict(count(0).next)
133 |     dist = defaultdict(count(0).next)
134 |     
135 |     pos['#UNKNOWN#']
136 |     dep['#UNKNOWN#']
137 |     dist['#UNKNOWN#']
138 | 
139 |     # Load the resource (processed corpus)
140 |     print 'Loading the corpus...'
141 |     corpus = Resources(corpus_prefix)
142 | 
143 |     keys = [(corpus.get_id_by_term(str(x)), corpus.get_id_by_term(str(y))) for (x, y) in dataset_keys]
144 |     patterns_x_to_y = [{ vectorize_path(path, lemma, pos, dep, dist, pre_trained_embs) : count
145 |                       for path, count in get_patterns(corpus, x_id, y_id).iteritems() }
146 |                     for (x_id, y_id) in keys]
147 |     patterns_x_to_y = [ { p : c for p, c in patterns_x_to_y[i].iteritems() if p is not None } for i in range(len(keys)) ]
148 | 
149 |     patterns = patterns_x_to_y
150 | 
151 |     empty = [dataset_keys[i] for i, path_list in enumerate(patterns) if len(path_list.keys()) == 0]
152 |     print 'Pairs without patterns:', len(empty), ', Dataset size:', len(dataset_keys)
153 | 
154 |     # Get the index for x and y (get a lemma index)
155 |     if words is None:
156 |         key_pairs = [(lemma[x], lemma[y]) for (x, y) in dataset_keys]
157 |     else:
158 |         key_pairs = [(lemma.get(x, 0), lemma.get(y, 0)) for (x, y) in dataset_keys]
159 | 
160 |     return key_pairs, patterns, lemma, pos, dep, dist
161 | 
162 | def get_patterns(corpus, x, y):
163 |     """
164 |     Get the paths between x and y
165 |     """
166 |     x_to_y_patterns = corpus.get_patterns(x, y)
167 |     patterns = { corpus.get_path_by_id(path) : count for (path, count) in x_to_y_patterns.iteritems() }
168 |     
169 |     return patterns
170 | 
171 | 
172 | def vectorize_path(path, lemma, pos, dep, dist, pre_trained_embs):
173 |     """
174 |     Returns a pattern
175 |     """
176 |     vectorized_path = [vectorize_node(node, lemma, pos, dep, dist, pre_trained_embs) for node in path.split(':::')]
177 |     if None in vectorized_path:
178 |         return None
179 |     else:
180 |         return tuple(vectorized_path)
181 | 
182 | def vectorize_node(node, lemma, pos, dep, dist, pre_trained_embs):
183 |     """
184 |     Returns a node: concatenate lemma/pos/dep/dist
185 |     """
186 |     try:
187 |         l, p, g, d = node.split('/')
188 |     except:
189 |         return None
190 |     
191 |     if pre_trained_embs:
192 |         return tuple([lemma.get(l, 0), pos[p], dep[g], dist[d]])
193 |     else:
194 |         return tuple([lemma[l], pos[p], dep[g], dist[d]])
195 | 
196 | def load_dataset(dataset_file):
197 |     """
198 |     Loads the dataset
199 |     """
200 |     with open(dataset_file, 'r') as fin:
201 |         lines = [tuple(line.strip().split('\t')) for line in fin]
202 |         random.shuffle(lines)
203 |         dataset = { (x, y) : label for (x, y, label) in lines }
204 | 
205 |     return dataset
206 | 
207 | def load_embeddings(file_name, vocab):
208 |     """
209 |     Load the pre-trained embeddings from a file
210 |     """
211 |     words = []
212 |     embs = []
213 |     
214 |     with open(file_name, 'rb') as f:
215 |         if file_name.endswith('.txt'):
216 |             header = to_unicode(f.readline())
217 |             if len(header.split()) == 2: vocab_size, vector_size = map(int, header.split())
218 |             elif len(header.split()) > 2:
219 |                 parts = header.rstrip().split(" ")
220 |                 word, vec = parts[0], list(map(numpy.float32, parts[1:]))
221 |                 words.append(to_unicode(word))
222 |                 embs.append(vec)
223 |             for _, line in enumerate(f):
224 |                 parts = to_unicode(line.rstrip()).split(" ")
225 |                 word, vec = parts[0], list(map(numpy.float32, parts[1:]))
226 |                 words.append(to_unicode(word))
227 |                 embs.append(vec)
228 |         elif file_name.endswith('.bin'):
229 |             header = to_unicode(f.readline())
230 |             vocab_size, vector_size = map(int, header.split())
231 |             binary_len = dtype(numpy.float32).itemsize * vector_size
232 |             for _ in range(vocab_size):
233 |                 word = []
234 |                 while True:
235 |                     ch = f.read(1)
236 |                     if ch == b' ':
237 |                         break
238 |                     if ch != b'\n':
239 |                         word.append(ch)
240 |                 word = to_unicode(b''.join(word))
241 |                 words.append(word)
242 |                 vec = fromstring(f.read(binary_len), dtype=numpy.float32)
243 |                 embs.append(vec)
244 |         else:
245 |             print "The extension of embeddings file is either .bin or .txt"
246 |     
247 |     # Add the unknown word
248 |     embs_dim = len(embs[1])
249 |     
250 |     for word in vocab.keys():
251 |         if word not in words:
252 |             words.append(word)
253 |             unk_vec = numpy.random.uniform(-0.25,0.25,embs_dim)
254 |             embs = numpy.vstack(embs, unk_vec)
255 |              
256 |     UNKNOWN_WORD = numpy.random.uniform(-0.25,0.25,embs_dim)
257 |     wv = numpy.vstack((UNKNOWN_WORD, embs))
258 |     words = ['#UNKNOWN#'] + list(words)
259 |     
260 |     word_index = { w : i for i, w in enumerate(words) }
261 | 
262 |     return wv, word_index
263 | 
264 | def to_unicode(text, encoding='utf8', errors='strict'):
265 |     """Convert a string (bytestring in `encoding` or unicode), to unicode."""
266 |     if isinstance(text, unicode):
267 |         return text
268 |     else:
269 |         return unicode(text, encoding=encoding, errors=errors)
270 |     


--------------------------------------------------------------------------------
/dataset/adjective-pairs.test:
--------------------------------------------------------------------------------
   1 | thick	stocky	0
   2 | unstressed	stressed	1
   3 | miraculous	natural	1
   4 | honest	incorruptible	0
   5 | fourth	4th	0
   6 | immaterial	material	1
   7 | conventional	unconventional	1
   8 | confusing	clear	1
   9 | indivisible	divisible	1
  10 | fissionable	fissile	0
  11 | unpaved	paved	1
  12 | key	central	0
  13 | obscure	esoteric	0
  14 | sad	gloomy	0
  15 | mathematical	questionable	1
  16 | dignified	majestic	0
  17 | weakened	strong	1
  18 | detached	attached	1
  19 | distinctive	typical	0
  20 | raw	polished	1
  21 | pompous	pretentious	0
  22 | special	limited	0
  23 | stupid	fat	0
  24 | calm	peaceful	0
  25 | bald	bearded	1
  26 | antagonistic	positive	1
  27 | diseased	sick	0
  28 | heavy	pregnant	0
  29 | hungry	thirsty	1
  30 | sterile	fertile	1
  31 | bright	brilliant	0
  32 | aerodynamic	streamlined	0
  33 | outspoken	blunt	0
  34 | right	incorrect	1
  35 | doubtful	sure	1
  36 | mechanical	mental	1
  37 | snowy	white	0
  38 | probable	unlikely	1
  39 | generous	stingy	1
  40 | poor	sufficient	1
  41 | unsaturated	saturated	1
  42 | wide	full	0
  43 | confident	shy	1
  44 | medial	distal	1
  45 | recent	low	0
  46 | unfair	fair	1
  47 | quick	swift	0
  48 | cheap	gaudy	0
  49 | tender	tough	1
  50 | white	pale	0
  51 | astronomical	little	1
  52 | slow	dull	0
  53 | northwestern	eastern	1
  54 | male	bad	0
  55 | intense	dull	1
  56 | defensive	offensive	1
  57 | ponderous	heavy	0
  58 | impermeable	permeable	1
  59 | unsure	certain	1
  60 | accurate	inaccurate	1
  61 | immoral	dishonest	0
  62 | spiritual	sensuous	1
  63 | shabby	new	1
  64 | offensive	abusive	0
  65 | poor	adequate	1
  66 | disagreeable	agreeable	1
  67 | written	oral	1
  68 | intimate	sexual	0
  69 | good	faulty	1
  70 | swampy	waterlogged	0
  71 | taut	close	0
  72 | civil	rude	1
  73 | elder	old	0
  74 | immovable	movable	1
  75 | small	uppercase	1
  76 | large	giant	0
  77 | sharp	gradual	1
  78 | oval	ovoid	0
  79 | numerical	qualitative	1
  80 | white	bare	1
  81 | lucky	unlucky	1
  82 | modern	new	0
  83 | juicy	succulent	0
  84 | oral	verbal	0
  85 | ample	small	1
  86 | open	shut	1
  87 | simple	direct	0
  88 | mesial	lateral	1
  89 | corresponding	different	1
  90 | permanent	constant	0
  91 | ambiguous	specific	1
  92 | bogus	fake	0
  93 | leeward	windward	1
  94 | patriotic	loyal	0
  95 | possible	potential	0
  96 | unsymmetrical	symmetrical	1
  97 | insistent	repetitive	0
  98 | morose	dark	0
  99 | open	overt	0
 100 | sad	heavy	0
 101 | dutiful	submissive	0
 102 | impure	pure	1
 103 | unlikely	unbelievable	0
 104 | nonalcoholic	alcoholic	1
 105 | shrill	high	0
 106 | blessed	damned	1
 107 | national	international	1
 108 | fertile	sterile	1
 109 | artless	simple	0
 110 | enlightening	informative	0
 111 | separate	distant	0
 112 | greedy	voracious	0
 113 | sharp	rigorous	0
 114 | byzantine	simple	1
 115 | reformist	conservative	1
 116 | conscious	aware	0
 117 | next	outgoing	1
 118 | small	fine	0
 119 | fragmented	united	1
 120 | flat	sharp	1
 121 | slim	fat	1
 122 | parallel	perpendicular	1
 123 | monetary	pecuniary	0
 124 | malignant	pernicious	0
 125 | cold	fresh	1
 126 | characteristic	uncharacteristic	1
 127 | loving	affectionate	0
 128 | secondary	basic	1
 129 | dirty	clean	1
 130 | hairy	bald	1
 131 | invulnerable	vulnerable	1
 132 | inept	useless	0
 133 | silly	plain	0
 134 | keen	bad	1
 135 | hilly	mountainous	0
 136 | dejected	despondent	0
 137 | true	unfaithful	1
 138 | glabrous	hairy	1
 139 | antitrust	unfair	1
 140 | massive	little	1
 141 | average	ordinary	0
 142 | general	diversified	1
 143 | grand	expansive	0
 144 | unitary	federal	1
 145 | compassionate	cruel	1
 146 | permanent	provisional	1
 147 | yellow	mean	0
 148 | impossible	possible	1
 149 | autonomous	dependent	1
 150 | wrong	accurate	1
 151 | annual	perennial	1
 152 | minuscule	little	0
 153 | pop	classic	1
 154 | baseless	unfounded	0
 155 | confident	insecure	1
 156 | augmentative	diminutive	1
 157 | complicated	simple	1
 158 | proficient	fluent	0
 159 | conclusive	convincing	0
 160 | monstrous	beautiful	1
 161 | live	hot	0
 162 | dark	good	1
 163 | judicial	illegal	1
 164 | mild	violent	1
 165 | rough	calm	1
 166 | conventional	atomic	1
 167 | radical	natural	0
 168 | slight	significant	1
 169 | narrow	bigoted	0
 170 | experimental	theoretical	1
 171 | deleterious	harmless	1
 172 | federal	local	1
 173 | former	latter	1
 174 | round	entire	0
 175 | exotic	alien	0
 176 | mental	psychical	0
 177 | old	jolly	0
 178 | eastern	western	1
 179 | noumenal	phenomenal	1
 180 | dull	loud	1
 181 | visible	perceptible	0
 182 | large	free	0
 183 | untested	old	1
 184 | permissible	impermissible	1
 185 | kind	mild	0
 186 | synergistic	antagonistic	1
 187 | menial	low	0
 188 | nameless	anonymous	0
 189 | unresponsive	responsive	1
 190 | real	unrealistic	1
 191 | dim	black	0
 192 | visual	optic	0
 193 | salutary	useful	0
 194 | generic	specific	1
 195 | legendary	unknown	1
 196 | intelligible	unintelligible	1
 197 | vicious	bad	0
 198 | loose	rambling	0
 199 | commercial	superior	1
 200 | relative	referential	0
 201 | giant	vast	0
 202 | mundane	extraordinary	1
 203 | swarthy	dark	0
 204 | wide	little	1
 205 | absolute	positive	0
 206 | confusing	distracting	0
 207 | charming	fascinating	0
 208 | excellent	golden	0
 209 | scientific	unscientific	1
 210 | coloured	natural	1
 211 | homogenous	heterogeneous	1
 212 | brave	warrior	0
 213 | offensive	annoying	0
 214 | wingless	winged	1
 215 | curly	straight	1
 216 | average	regular	0
 217 | grey	northern	1
 218 | ordinary	average	0
 219 | imaginative	visionary	0
 220 | aggressive	nonaggressive	1
 221 | fractional	whole	1
 222 | plain	decorated	1
 223 | needy	destitute	0
 224 | fat	greasy	0
 225 | expressive	forceful	0
 226 | obsolete	recent	1
 227 | awful	nice	1
 228 | ashen	white	0
 229 | financial	fiscal	0
 230 | good	real	0
 231 | gaseous	solid	1
 232 | flawed	perfect	1
 233 | haired	hairless	1
 234 | dependent	independent	1
 235 | grotesque	beautiful	1
 236 | pregnant	nonpregnant	1
 237 | eligible	desirable	0
 238 | independent	free	0
 239 | longitudinal	transverse	1
 240 | firstborn	eldest	0
 241 | small	minor	0
 242 | liquid	illiquid	1
 243 | royal	noble	0
 244 | lively	alert	0
 245 | necessary	inevitable	0
 246 | united	single	1
 247 | rich	copious	0
 248 | indefinite	indeterminate	0
 249 | blue	clean	1
 250 | individual	joint	1
 251 | high	low	1
 252 | indisputable	certain	0
 253 | tight	easy	1
 254 | organized	unorganized	1
 255 | unmarried	celibate	0
 256 | unclean	clean	1
 257 | easy	smooth	0
 258 | parallel	equal	0
 259 | disproportionate	proportionate	1
 260 | huge	little	1
 261 | slow	active	1
 262 | free	spare	0
 263 | interested	concerned	0
 264 | honorable	dishonorable	1
 265 | terminal	intermediate	1
 266 | rich	precious	0
 267 | inclusive	exclusive	1
 268 | military	civilian	1
 269 | odd	strange	0
 270 | ordinary	wonderful	1
 271 | omnivorous	carnivorous	1
 272 | despondent	dejected	0
 273 | negative	indirect	0
 274 | thin	small	0
 275 | allochthonous	autochthonous	1
 276 | irritable	irascible	0
 277 | inflexible	rigid	0
 278 | mental	material	1
 279 | little	old	1
 280 | costly	rich	0
 281 | original	initial	0
 282 | astonishing	surprising	0
 283 | textured	smooth	1
 284 | sorry	poor	0
 285 | popular	pop	0
 286 | immoral	impure	0
 287 | competitive	socialist	1
 288 | oral	aboral	1
 289 | stern	severe	0
 290 | fraternal	identical	1
 291 | sedentary	active	1
 292 | wild	violent	0
 293 | inevitable	unpredictable	1
 294 | sound	healthy	0
 295 | prenatal	perinatal	1
 296 | planetary	epicyclic	0
 297 | slow	smart	1
 298 | capricious	arbitrary	0
 299 | green	sophisticated	1
 300 | unadorned	bare	0
 301 | miniature	large	1
 302 | theoretical	applied	1
 303 | ready	about	0
 304 | notable	noteworthy	0
 305 | useful	harmful	1
 306 | strong	powerful	0
 307 | delicate	soft	0
 308 | nomadic	settled	1
 309 | sudden	immediate	0
 310 | high	powerful	0
 311 | unwieldy	cumbersome	0
 312 | honest	reliable	0
 313 | unwieldy	practical	1
 314 | public	private	1
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1000 | countless	infinite	0
1001 | initial	last	1
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1003 | many	few	1
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1008 | powdery	loose	0
1009 | clever	cunning	0
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1013 | greenish	green	0
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1016 | amphibious	terrestrial	1
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1020 | ordinary	normal	0
1021 | atmospheric	aerial	0
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1024 | ingressive	egressive	1
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1028 | certain	true	0
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1067 | conventional	nuclear	1
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1071 | serious	frivolous	1
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1073 | useful	profitable	0
1074 | regressive	progressive	1
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1076 | heated	hot	0
1077 | courageous	daring	0
1078 | elementary	introductory	0
1079 | colored	uncolored	1
1080 | singular	rare	0
1081 | sinister	menacing	0
1082 | eldest	firstborn	0
1083 | dutiful	obedient	0
1084 | equal	even	0
1085 | tight	brisk	0
1086 | brutal	vicious	0
1087 | implicit	inherent	0
1088 | brittle	strong	1
1089 | hydrated	anhydrous	1
1090 | iffy	sure	1
1091 | long	sound	1
1092 | wiry	tough	0
1093 | actinomorphic	zygomorphic	1
1094 | pale	dim	0
1095 | meridian	prime	0
1096 | military	nonmilitary	1
1097 | rich	wealthy	0
1098 | harmonic	musical	0
1099 | effective	ineffective	1
1100 | arrogant	condescending	1
1101 | secure	insecure	1
1102 | tender	old	1
1103 | supernatural	metaphysical	0
1104 | wide	skinny	1
1105 | excessive	unreasonable	0
1106 | graphical	graphic	0
1107 | majestic	dignified	0
1108 | tender	compassionate	0
1109 | fond	tender	0
1110 | resident	certain	0
1111 | pure	simple	0
1112 | prewar	postwar	1
1113 | argent	white	0
1114 | average	mean	0
1115 | analytic	synthetic	1
1116 | royal	regal	0
1117 | nomothetic	idiographic	1
1118 | restricted	unrestricted	1
1119 | inner	outward	1
1120 | sweet	sour	1
1121 | lengthy	long	0
1122 | sullen	morose	0
1123 | heterogeneous	mixed	0
1124 | psychical	physical	1
1125 | first	last	1
1126 | thin	slim	0
1127 | tedious	dull	0
1128 | modern	ancient	1
1129 | northbound	south	1
1130 | pictorial	graphic	0
1131 | great	numerous	0
1132 | filial	parental	1
1133 | ambivalent	certain	1
1134 | fast	speedy	0
1135 | amateur	recreational	0
1136 | specific	widespread	1
1137 | analogous	parallel	0
1138 | likely	unlikely	1
1139 | real	nominal	1
1140 | diffuse	wide	0
1141 | deceptive	false	0
1142 | contagious	infectious	0
1143 | perfidious	treacherous	0
1144 | identical	different	1
1145 | rich	thin	1
1146 | angry	red	0
1147 | red	uncoloured	1
1148 | individual	mutual	1
1149 | victorian	modern	1
1150 | odd	weird	0
1151 | north	south	1
1152 | medieval	modern	1
1153 | usable	unusable	1
1154 | teenage	teen	0
1155 | literal	real	0
1156 | cryptic	hidden	0
1157 | municipal	foreign	1
1158 | virulent	deadly	0
1159 | generous	spirited	0
1160 | full	incomplete	1
1161 | specific	gross	1
1162 | famous	historical	0
1163 | particular	exact	0
1164 | typical	atypical	1
1165 | off	active	1
1166 | satisfactory	unsatisfactory	1
1167 | rancid	sour	0
1168 | subordinate	main	1
1169 | mysterious	dark	0
1170 | offshore	onshore	1
1171 | offensive	disagreeable	0
1172 | several	particular	0
1173 | glorious	noble	0
1174 | fair	foul	1
1175 | unaware	aware	1
1176 | painful	sore	0
1177 | colored	colorful	0
1178 | rare	abundant	1
1179 | northern	southern	1
1180 | heroic	gallant	0
1181 | rounded	spherical	0
1182 | harmonic	consonant	0
1183 | renewable	exhaustible	1
1184 | stubborn	harsh	0
1185 | somber	dark	0
1186 | tempting	attractive	0
1187 | surprising	unsurprising	1
1188 | nice	awful	1
1189 | sensitive	unclassified	1
1190 | underlying	explicit	1
1191 | everyday	extraordinary	1
1192 | fearful	good	1
1193 | extreme	moderate	1
1194 | only	inclusive	1
1195 | amicable	hostile	1
1196 | dead	alive	1
1197 | soluble	insoluble	1
1198 | honest	honorable	0
1199 | successful	happy	0
1200 | childish	old	1
1201 | nonfinancial	financial	1
1202 | casual	difficult	1
1203 | triangular	rounded	1
1204 | compulsory	optional	1
1205 | casual	heavy	1
1206 | underprivileged	privileged	1
1207 | solitary	alone	0
1208 | viviparous	ovoviviparous	1
1209 | purgative	cathartic	0
1210 | contemplative	thoughtful	0
1211 | light	deep	1
1212 | gargantuan	small	1
1213 | abundant	big	0
1214 | blind	sighted	1
1215 | wise	unwise	1
1216 | tenth	10th	0
1217 | special	scheduled	1
1218 | ancient	young	1
1219 | spinal	vertebral	0
1220 | sick	demented	0
1221 | neighborly	friendly	0
1222 | literary	informal	1
1223 | pejorative	complimentary	1
1224 | mean	rich	1
1225 | avirulent	virulent	1
1226 | irresponsible	responsible	1
1227 | irritated	annoyed	0
1228 | lingual	buccal	1
1229 | hairy	bare	1
1230 | likeable	sympathetic	0
1231 | giant	small	1
1232 | thick	dense	0
1233 | prostrate	vertical	1
1234 | forthright	frank	0
1235 | important	anxious	0
1236 | fast	wild	0
1237 | imperfect	complete	1
1238 | candid	white	0
1239 | diluted	concentrated	1
1240 | monomeric	polymeric	1
1241 | clear	indistinct	1
1242 | volatile	explosive	0
1243 | attributive	predicative	1
1244 | valuable	worthless	1
1245 | little	much	1
1246 | upper	side	1
1247 | active	quiet	1
1248 | lentic	lotic	1
1249 | dorsal	neural	0
1250 | classical	correct	0
1251 | anxious	distressed	0
1252 | lean	thin	0
1253 | mountainous	little	1
1254 | undergraduate	postgraduate	1
1255 | tall	splendid	0
1256 | dull	lively	1
1257 | elementary	primary	0
1258 | rough	stormy	0
1259 | anaerobic	aerobic	1
1260 | concentrated	intense	0
1261 | instinctive	spontaneous	0
1262 | intentional	deliberate	0
1263 | supersonic	sonic	1
1264 | medial	intermediate	0
1265 | fatal	deadly	0
1266 | colored	natural	1
1267 | open	enclosed	1
1268 | courteous	affable	0
1269 | pluperfect	imperfect	1
1270 | imminent	immediate	0
1271 | incorrect	correct	1
1272 | big	light	1
1273 | long	short	1
1274 | able	effective	0
1275 | skinny	loose	1
1276 | violent	peaceful	1
1277 | muddy	murky	0
1278 | compressed	flat	0
1279 | prostrate	upright	1
1280 | open	fine	1
1281 | full	empty	1
1282 | calm	collected	0
1283 | adaxial	abaxial	1
1284 | regular	irregular	1
1285 | hermaphrodite	female	1
1286 | relative	disproportionate	1
1287 | separate	different	0
1288 | registered	unregistered	1
1289 | faint	dim	0
1290 | cyclic	circular	0
1291 | immediate	close	0
1292 | further	close	1
1293 | general	common	0
1294 | integral	complete	0
1295 | right	inappropriate	1
1296 | perfective	imperfective	1
1297 | honest	chaste	0
1298 | idle	lazy	0
1299 | fictional	fabricated	0
1300 | plain	natural	0
1301 | clean	dirty	1
1302 | quiet	loud	1
1303 | foggy	misty	0
1304 | impious	pious	1
1305 | hazy	clear	1
1306 | sincere	genuine	0
1307 | pious	righteous	0
1308 | poor	good	1
1309 | bluish	neutral	1
1310 | polyandrous	monogamous	1
1311 | cunning	clever	0
1312 | prominent	invisible	1
1313 | urbane	polite	0
1314 | ripe	good	0
1315 | gritty	fine	1
1316 | cruel	brutal	0
1317 | oriental	eastern	0
1318 | playful	earnest	1
1319 | old	erstwhile	0
1320 | easy	unavailable	1
1321 | undisputed	controversial	1
1322 | cloudless	clear	0
1323 | unpretentious	simple	0
1324 | affectionate	sharp	1
1325 | sexual	asexual	1
1326 | reducible	irreducible	1
1327 | striking	impressive	0
1328 | spiritual	natural	1
1329 | progressive	reformist	0
1330 | unspecified	specified	1
1331 | metaphysical	abstract	0
1332 | dry	ironic	0
1333 | unadjusted	adjusted	1
1334 | angry	indignant	0
1335 | rhythmic	metrical	0
1336 | naked	clad	1
1337 | fitted	ready	0
1338 | irregular	regular	1
1339 | passionate	warm	0
1340 | heliocentric	geocentric	1
1341 | incorrupt	pure	0
1342 | pleased	angry	1
1343 | imperfect	perfect	1
1344 | human	superhuman	1
1345 | principal	assistant	1
1346 | wealthy	impoverished	1
1347 | high	eminent	0
1348 | robust	vigorous	0
1349 | main	principal	0
1350 | objective	abstract	1
1351 | violent	smart	0
1352 | impartial	biased	1
1353 | noble	plebeian	1
1354 | full	wide	0
1355 | tired	fatigued	0
1356 | weak	skilled	1
1357 | integral	fractional	1
1358 | mysterious	inexplicable	0
1359 | dreary	drab	0
1360 | suitable	appropriate	0
1361 | bound	free	1
1362 | dry	productive	1
1363 | native	strange	1
1364 | extrinsic	intrinsic	1
1365 | damp	moist	0
1366 | tall	short	1
1367 | legislative	executive	1
1368 | simple	fancy	1
1369 | common	uncommon	1
1370 | terrestrial	planetary	0
1371 | familiar	unusual	1
1372 | righteous	unrighteous	1
1373 | silly	shallow	0
1374 | conspicuous	brilliant	0
1375 | equipped	unequipped	1
1376 | latter	former	1
1377 | diffuse	hard	1
1378 | honest	moral	0
1379 | potential	actual	1
1380 | impressive	effective	0
1381 | fantastic	real	1
1382 | mediocre	ordinary	0
1383 | accurate	careful	0
1384 | unfavorable	good	1
1385 | sprightly	gay	0
1386 | broken	complete	1
1387 | agile	active	0
1388 | vital	critical	0
1389 | historic	future	1
1390 | concerned	unconcerned	1
1391 | disrespectful	contemptuous	0
1392 | dull	gloomy	0
1393 | awake	asleep	1
1394 | gelatinous	thin	1
1395 | strict	lax	1
1396 | marked	conspicuous	0
1397 | intellectual	emotional	1
1398 | multidimensional	unidimensional	1
1399 | realistic	unrealistic	1
1400 | sorrowful	joyful	1
1401 | sympathetic	likable	0
1402 | planned	unplanned	1
1403 | righteous	virtuous	0
1404 | incapable	incompetent	0
1405 | distant	cold	0
1406 | weak	irregular	1
1407 | soft	heavy	1
1408 | internal	outward	1
1409 | light	fatty	1
1410 | separate	alone	0
1411 | objective	outward	0
1412 | insipid	flat	0
1413 | dominant	recessive	1
1414 | philanthropic	humanitarian	0
1415 | miserable	happy	1
1416 | reflective	contemplative	0
1417 | agile	quick	0
1418 | supreme	inferior	1
1419 | even	odd	1
1420 | cruel	hard	0
1421 | ambiguous	precise	1
1422 | accurate	faithful	0
1423 | vulnerable	strong	1
1424 | disadvantageous	advantageous	1
1425 | illegitimate	legitimate	1
1426 | monastic	secular	1
1427 | perennial	biennial	1
1428 | routine	mundane	0
1429 | violent	red	0
1430 | heavy	ponderous	0
1431 | pervious	impervious	1
1432 | philanthropic	benevolent	0
1433 | observational	theoretical	1
1434 | unclassified	classified	1
1435 | modern	old	1
1436 | western	westward	0
1437 | dead	live	1
1438 | counterrevolutionary	revolutionary	1
1439 | idle	active	1
1440 | specific	broad	1
1441 | rectal	anal	0
1442 | opaque	bright	1
1443 | unfit	fit	1
1444 | courageous	gallant	0
1445 | archaic	late	1
1446 | malaysian	malay	0
1447 | retrograde	anterograde	1
1448 | pliant	flexible	0
1449 | little	brief	0
1450 | characteristic	diagnostic	0
1451 | cheap	expensive	1
1452 | incapable	capable	1
1453 | foolish	simple	0
1454 | ill	well	1
1455 | fine	finished	0
1456 | musical	melodic	0
1457 | southeastern	western	1
1458 | unflappable	cool	0
1459 | intercollegiate	intramural	1
1460 | criminal	innocent	1
1461 | solid	strong	0
1462 | vernacular	everyday	0
1463 | unfettered	free	0
1464 | casual	contingent	0
1465 | vague	indefinite	0
1466 | absurd	inconsistent	0
1467 | illiterate	ignorant	0
1468 | monoclinic	triclinic	1
1469 | green	greenish	0
1470 | desirable	undesirable	1
1471 | innumerate	illiterate	1
1472 | similar	dissimilar	1
1473 | rough	easy	1
1474 | comfortable	cheerful	0
1475 | direct	secondary	1
1476 | intelligent	stupid	1
1477 | tough	comfortable	1
1478 | slight	important	1
1479 | wrong	proper	1
1480 | cordial	warm	0
1481 | stormy	tempestuous	0
1482 | undeveloped	developed	1
1483 | serrated	toothed	0
1484 | intentional	free	0
1485 | individual	definite	0
1486 | hard	formal	0
1487 | rational	irrational	1
1488 | subterminal	terminal	1
1489 | faithful	upright	0
1490 | endogenous	exogenous	1
1491 | erroneous	incorrect	0
1492 | contrary	hostile	0
1493 | dull	bright	1
1494 | severe	extreme	0
1495 | prismatic	colorless	1
1496 | harmful	harmless	1
1497 | undercover	clandestine	0
1498 | congenital	hereditary	0
1499 | exact	true	0
1500 | incapable	unable	0
1501 | false	natural	1
1502 | absolute	incomplete	1
1503 | poor	fortunate	1
1504 | correct	wrong	1
1505 | feminine	masculine	1
1506 | savage	wild	0
1507 | lipophilic	hydrophilic	1
1508 | abnormal	odd	0
1509 | hairy	hairless	1
1510 | analytical	synthetical	1
1511 | westerly	east	1
1512 | unfortunate	fortunate	1
1513 | oppressive	heavy	0
1514 | artificial	organic	1
1515 | idiosyncratic	common	1
1516 | negative	constructive	1
1517 | poor	pathetic	0
1518 | cold	hot	1
1519 | honest	righteous	0
1520 | heroic	valiant	0
1521 | dark	dingy	0
1522 | headless	acephalous	0
1523 | cooperative	competitive	1
1524 | good	friendly	0
1525 | nitrous	nitric	0
1526 | capricious	whimsical	0
1527 | hard	soft	1
1528 | miscible	immiscible	1
1529 | favourable	unfavourable	1
1530 | nonviolent	violent	1
1531 | aware	informed	0
1532 | cultured	civilized	0
1533 | quiescent	active	1
1534 | mixed	interracial	0
1535 | alliterative	unrhymed	1
1536 | destitute	barren	0
1537 | main	cardinal	0
1538 | contradictory	opposite	0
1539 | substantial	square	0
1540 | turbulent	violent	0
1541 | catchy	easy	1
1542 | free	paid	1
1543 | open	split	0
1544 | bleak	stark	0
1545 | profound	mild	1
1546 | first	1st	0
1547 | threatening	sinister	0
1548 | insoluble	soluble	1
1549 | devout	sincere	0
1550 | rugged	smooth	1
1551 | orthodox	unorthodox	1
1552 | frozen	fresh	1
1553 | diminished	small	0
1554 | red	carmine	0
1555 | material	important	0
1556 | widowed	married	1
1557 | sad	depressed	0
1558 | atheistic	religious	1
1559 | heroic	desperate	0
1560 | tough	rowdy	0
1561 | gargantuan	huge	0
1562 | advantageous	useful	0
1563 | unprofessional	professional	1
1564 | obtuse	blunt	0
1565 | visionary	fantastic	0
1566 | recreational	amateur	0
1567 | excellent	bad	1
1568 | soft	fit	1
1569 | disorderly	irregular	0
1570 | tired	exhausted	0
1571 | calm	composed	0
1572 | impulsive	cautious	1
1573 | dull	saturated	1
1574 | good	healthy	0
1575 | legitimate	real	0
1576 | level	steady	0
1577 | anxious	uneasy	0
1578 | bloody	bloodless	1
1579 | complex	intricate	0
1580 | intractable	tractable	1
1581 | familiar	unknown	1
1582 | new	accustomed	1
1583 | cute	clever	0
1584 | arbitrary	tyrannical	0
1585 | nice	nasty	1
1586 | honest	genuine	0
1587 | paranormal	psychic	0
1588 | handsome	ugly	1
1589 | endless	infinite	0
1590 | sharp	low	1
1591 | steep	heavy	0
1592 | extravagant	exuberant	0
1593 | active	stative	1
1594 | changeable	unchangeable	1
1595 | unbroken	broken	1
1596 | steep	moderate	1
1597 | inverse	forward	1
1598 | genuine	fake	1
1599 | clumsy	skilled	1
1600 | durable	short	1
1601 | teen	old	1
1602 | despicable	vile	0
1603 | rigorous	severe	0
1604 | intrepid	daring	0
1605 | solid	sound	0
1606 | out	inner	1
1607 | frequentative	iterative	0
1608 | unambiguous	ambiguous	1
1609 | spiritual	worldly	1
1610 | helical	straight	1
1611 | exact	inexact	1
1612 | evil	good	1
1613 | peculiar	familiar	1
1614 | retail	wholesale	1
1615 | perfect	whole	0
1616 | transonic	subsonic	1
1617 | weighty	light	1
1618 | extrusive	intrusive	1
1619 | minor	small	0
1620 | omnivorous	insectivorous	1
1621 | witty	smart	0
1622 | unmarked	marked	1
1623 | tender	gentle	0
1624 | gymnastic	athletic	0
1625 | yellowish	yellow	0
1626 | forward	reverse	1
1627 | profitable	useful	0
1628 | abrupt	unexpected	0
1629 | caustic	bitter	0
1630 | figured	plain	1
1631 | unconcerned	indifferent	0
1632 | tolerant	intolerant	1
1633 | altricial	precocial	1
1634 | vague	obscure	0
1635 | fast	quick	0
1636 | trivial	little	0
1637 | senior	junior	1
1638 | small	harsh	1
1639 | unethical	ethical	1
1640 | bottom	best	1
1641 | periodical	quarterly	0
1642 | stark	bleak	0
1643 | infrequent	rare	0
1644 | moist	wet	0
1645 | equipped	furnished	0
1646 | forensic	legal	0
1647 | clandestine	secretive	0
1648 | cold	alive	1
1649 | normal	original	0
1650 | sleepy	awake	1
1651 | lax	tense	1
1652 | uncivilised	barbaric	0
1653 | unchangeable	changeable	1
1654 | conditional	unconditional	1
1655 | recent	future	1
1656 | spiritual	earthly	1
1657 | vague	undefined	0
1658 | postnatal	prenatal	1
1659 | soggy	wet	0
1660 | final	unappealable	0
1661 | unintelligent	intelligent	1
1662 | universal	worldwide	0
1663 | rational	sensible	0
1664 | dim	bright	1
1665 | valid	expired	1
1666 | combative	contentious	0
1667 | affectionate	fond	0
1668 | clandestine	overt	1
1669 | heavy	lively	1
1670 | subterranean	underground	0
1671 | residential	nonresidential	1
1672 | diverse	same	1
1673 | spirited	bold	0
1674 | gay	strict	1
1675 | phonetic	ideographic	1
1676 | wanton	reckless	0
1677 | extraordinary	abnormal	0
1678 | singular	individual	0
1679 | gross	large	0
1680 | left	odd	0
1681 | blue	blueish	0
1682 | necessary	unnecessary	1
1683 | hot	passionate	0
1684 | immediate	ultimate	1
1685 | sinful	righteous	1
1686 | free	fixed	1
1687 | left	right	1
1688 | dismal	gloomy	0
1689 | fruitful	rich	0
1690 | endemic	epidemic	1
1691 | sour	tart	0
1692 | rapid	sharp	0
1693 | unconscious	conscious	1
1694 | vibrant	resonant	0
1695 | lineal	collateral	1
1696 | fast	easy	0
1697 | intact	affected	1
1698 | rude	late	1
1699 | illegitimate	legal	1
1700 | drunk	sober	1
1701 | simple	sophisticated	1
1702 | operative	medical	1
1703 | medical	surgical	1
1704 | outgoing	sociable	0
1705 | humorous	jocular	0
1706 | pleasing	delightful	0
1707 | edgy	sharp	0
1708 | nonstandard	standard	1
1709 | abrasive	smooth	1
1710 | steady	firm	0
1711 | persistent	constant	0
1712 | keen	eager	0
1713 | alternative	alternate	0
1714 | new	fresh	0
1715 | average	uncommon	1
1716 | gray	northern	1
1717 | liberal	catholic	0
1718 | anglican	english	0
1719 | wicked	mischievous	0
1720 | official	unconfirmed	1
1721 | unhappy	sad	0
1722 | structural	architectural	0
1723 | oblique	parallel	1
1724 | abstract	whole	1
1725 | odd	eccentric	0
1726 | significant	token	0
1727 | subconscious	conscious	1
1728 | difficult	hard	0
1729 | wealthy	poor	1
1730 | clear	qualified	1
1731 | dramatic	burlesque	0
1732 | true	pure	0
1733 | senior	superior	0
1734 | impossible	probable	1
1735 | flat	inclined	1
1736 | insufficient	inefficient	0
1737 | safe	whole	0
1738 | usual	special	1
1739 | prevalent	predominant	0
1740 | exoteric	esoteric	1
1741 | northern	south	1
1742 | diseased	healthy	1
1743 | feminine	female	0
1744 | green	mature	1
1745 | awkward	easy	1
1746 | strange	new	0
1747 | physical	supernatural	1
1748 | outlandish	bizarre	0
1749 | outdated	antiquated	0
1750 | volatile	nonvolatile	1
1751 | advanced	innovative	0
1752 | wholesome	sweet	0
1753 | mere	simple	0
1754 | extinct	extant	1
1755 | improved	unimproved	1
1756 | high	arrogant	0
1757 | ecclesiastical	religious	0
1758 | moral	material	1
1759 | fresh	stale	1
1760 | dark	light	1
1761 | indirect	oblique	0
1762 | whole	gross	0
1763 | mediaeval	modern	1
1764 | nucleophilic	electrophilic	1
1765 | steady	constant	0
1766 | poignant	touching	0
1767 | unwelcome	welcome	1
1768 | natural	innate	0
1769 | invalid	void	0
1770 | obstinate	stubborn	0
1771 | derivational	inflectional	1
1772 | tired	fresh	1
1773 | yellow	new	1
1774 | material	mental	1
1775 | probable	likely	0
1776 | gloomy	sad	0
1777 | red	ruby	0
1778 | experiential	theoretical	1
1779 | potential	likely	0
1780 | clean	difficult	1
1781 | calm	nervous	1
1782 | firm	steadfast	0
1783 | beloved	dear	0
1784 | interior	internal	0
1785 | bombastic	turgid	0
1786 | loud	cheap	0
1787 | worldly	spiritual	1
1788 | voiced	voiceless	1
1789 | roomy	broad	0
1790 | conjunct	disjunct	1
1791 | unlawful	illegal	0
1792 | painful	difficult	0
1793 | private	separate	0
1794 | primitive	civilized	1
1795 | trashy	cheap	0
1796 | italic	upright	1
1797 | simple	difficult	1
1798 | hollow	low	0
1799 | internal	national	0
1800 | near	far	1
1801 | hispanic	latino	0
1802 | denticulate	smooth	1
1803 | aggressive	combative	0
1804 | adolescent	old	1
1805 | expensive	lavish	0
1806 | surreal	real	1
1807 | indoor	outdoor	1
1808 | polar	icy	0
1809 | colloquial	conversational	0
1810 | tough	hardy	0
1811 | clean	complete	0
1812 | accurate	precise	0
1813 | unusual	familiar	1
1814 | odd	unusual	0
1815 | present	immediate	0
1816 | shy	wary	0
1817 | famous	distinguished	0
1818 | radiant	luminous	0
1819 | bipartisan	partisan	1
1820 | circumpolar	invisible	1
1821 | spectacular	dramatic	0
1822 | broad	vast	0
1823 | profane	sacred	1
1824 | remote	distant	0
1825 | postwar	prewar	1
1826 | bisexual	heterosexual	1
1827 | professional	unprofessional	1
1828 | courageous	enterprising	0
1829 | bizarre	whimsical	0
1830 | deep	thorough	0
1831 | normal	reverse	1
1832 | sound	whole	0
1833 | comparative	absolute	1
1834 | low	degraded	0
1835 | popular	uncommon	1
1836 | near	ready	0
1837 | formal	precise	0
1838 | strange	unusual	0
1839 | childish	immature	0
1840 | galactic	little	1
1841 | mutual	individual	1
1842 | perpendicular	normal	0
1843 | antique	old	0
1844 | active	passive	1
1845 | insignificant	major	1
1846 | savory	spicy	0
1847 | angular	curved	1
1848 | broad	extensive	0
1849 | hermaphroditic	female	1
1850 | regional	sectional	0
1851 | small	coarse	1
1852 | sighted	blind	1
1853 | strong	warm	0
1854 | aware	unaware	1
1855 | intuitive	counterintuitive	1
1856 | farther	close	1
1857 | essential	inessential	1
1858 | frozen	hot	1
1859 | incorrect	wrong	0
1860 | christian	pagan	1
1861 | secondary	second	0
1862 | weak	robust	1
1863 | vital	lively	0
1864 | sloppy	slapdash	0
1865 | munificent	generous	0
1866 | handsome	generous	0
1867 | thin	full	1
1868 | marvelous	fantastic	0
1869 | legal	invalid	1
1870 | exact	precise	0
1871 | delicate	fragile	0
1872 | gentle	mild	0
1873 | strict	tense	0
1874 | friendly	favorable	0
1875 | atypical	typical	1
1876 | volatile	stable	1
1877 | shy	confident	1
1878 | scenic	theatrical	0
1879 | aristocratic	gentle	0
1880 | flexuous	straight	1
1881 | curable	incurable	1
1882 | goofy	regular	1
1883 | religious	profane	1
1884 | long	brief	1
1885 | clean	impure	1
1886 | ingenious	witty	0
1887 | genitive	possessive	0
1888 | theoretic	empirical	1
1889 | thin	lean	0
1890 | pitiable	poor	0
1891 | modern	classic	1
1892 | financial	nonfinancial	1
1893 | friendly	amicable	0
1894 | important	trivial	1
1895 | unfaithful	faithful	1
1896 | rigid	stiff	0
1897 | incapable	deficient	0
1898 | stiff	flexible	1
1899 | sumptuous	grand	0
1900 | crucial	important	0
1901 | 17th	seventeenth	0
1902 | authentic	counterfeit	1
1903 | vulgar	common	0
1904 | dysfunctional	functional	1
1905 | southwestern	north	1
1906 | youthful	fresh	0
1907 | cool	dispassionate	0
1908 | wee	little	0
1909 | retrospective	prospective	1
1910 | cheap	superior	1
1911 | sweet	gentle	0
1912 | active	vigorous	0
1913 | difficult	easy	1
1914 | hydrophobic	hydrophilic	1
1915 | bloody	cruel	0
1916 | unqualified	qualified	1
1917 | unified	coordinated	0
1918 | routine	unremarkable	0
1919 | bitter	sharp	0
1920 | tight	neat	0
1921 | foster	biological	1
1922 | raspy	hoarse	0
1923 | realistic	utopian	1
1924 | original	derivative	1
1925 | open	exposed	0
1926 | elliptical	elliptic	0
1927 | controllable	uncontrollable	1
1928 | hostile	amicable	1
1929 | tremendous	fantastic	0
1930 | opulent	wealthy	0
1931 | mindful	careful	0
1932 | fragmentary	whole	1
1933 | skinny	fat	1
1934 | wide	extended	0
1935 | quarter	fourth	0
1936 | powerful	weak	1
1937 | capital	great	0
1938 | altricial	nidicolous	0
1939 | uneducated	educated	1
1940 | greek	hellenic	0
1941 | athletic	gymnastic	0
1942 | legal	sound	0
1943 | unacceptable	unpleasant	0
1944 | adjacent	separate	1
1945 | formless	shapeless	0
1946 | frank	direct	0
1947 | vivid	bright	0
1948 | intact	entire	0
1949 | fragrant	aromatic	0
1950 | transient	lasting	1
1951 | analogous	opposite	1
1952 | rugged	uneven	0
1953 | stupid	inane	0
1954 | individual	single	0
1955 | muslim	islamic	0
1956 | rabbinic	rabbinical	0
1957 | supernatural	superhuman	0
1958 | wrongful	unlawful	0
1959 | merciful	cruel	1
1960 | sympatric	allopatric	1
1961 | intermittent	recurrent	0
1962 | wet	dry	1
1963 | covert	private	0
1964 | noninfectious	infectious	1
1965 | deep	shallow	1
1966 | hopeless	good	1
1967 | obedient	dutiful	0
1968 | dynamic	stative	1
1969 | logical	coherent	0
1970 | open	extended	0
1971 | binary	boolean	0
1972 | southern	north	1
1973 | extramural	intramural	1
1974 | sorry	hurt	0
1975 | verbatim	direct	0
1976 | statuesque	short	1
1977 | grateful	appreciative	0
1978 | introspective	subjective	0
1979 | honest	sincere	0
1980 | uneducated	illiterate	0
1981 | easy	uncomfortable	1
1982 | weighty	serious	0
1983 | artificial	theatrical	0
1984 | aged	new	1
1985 | organic	inorganic	1
1986 | human	mortal	0
1987 | 


--------------------------------------------------------------------------------
/dataset/adjective-pairs.val:
--------------------------------------------------------------------------------
  1 | innocent	harmless	0
  2 | noble	ignoble	1
  3 | good	awful	1
  4 | easy	heavy	1
  5 | stupid	smart	1
  6 | greedy	avaricious	0
  7 | indirect	immediate	1
  8 | trivial	ordinary	0
  9 | affective	emotional	0
 10 | torpid	dull	0
 11 | linear	digital	1
 12 | saline	salty	0
 13 | perfect	certain	0
 14 | actual	substantial	0
 15 | simplistic	complex	1
 16 | indigenous	aboriginal	0
 17 | unremarkable	routine	0
 18 | usual	unusual	1
 19 | transparent	crystalline	0
 20 | stately	dignified	0
 21 | beautiful	great	0
 22 | unlawful	unconstitutional	0
 23 | graphic	vivid	0
 24 | rectangular	rounded	1
 25 | vast	cosmic	0
 26 | thin	fragile	0
 27 | waterlogged	dry	1
 28 | extensive	widespread	0
 29 | hot	cool	1
 30 | academic	applied	1
 31 | transparent	open	0
 32 | incompatible	inconsistent	0
 33 | disparate	same	1
 34 | separate	integrated	1
 35 | radical	old	1
 36 | double	little	1
 37 | authoritarian	autocratic	0
 38 | fierce	furious	0
 39 | foolish	silly	0
 40 | homozygous	heterozygous	1
 41 | distinguishable	distinct	0
 42 | intrinsic	extrinsic	1
 43 | clever	adroit	0
 44 | sweet	perfumed	0
 45 | diachronic	synchronic	1
 46 | incompressible	compressible	1
 47 | nonresidential	residential	1
 48 | conspicuous	famous	0
 49 | provincial	cosmopolitan	1
 50 | dreary	dark	0
 51 | adoptive	biological	1
 52 | foolhardy	reckless	0
 53 | aged	fresh	1
 54 | sure	false	1
 55 | invisible	visible	1
 56 | poor	unfortunate	0
 57 | apparent	plain	0
 58 | live	dead	1
 59 | tangy	sweet	1
 60 | prefrontal	posterior	1
 61 | dumb	slow	0
 62 | plain	decorative	1
 63 | leaded	unleaded	1
 64 | warm	cold	1
 65 | harsh	severe	0
 66 | narrow	strait	0
 67 | special	extraordinary	0
 68 | plebeian	patrician	1
 69 | stationary	stable	0
 70 | common	familiar	0
 71 | unimportant	insignificant	0
 72 | stupid	clever	1
 73 | close	harsh	1
 74 | bottom	top	1
 75 | makeshift	permanent	1
 76 | terrific	terrible	0
 77 | large	minuscule	1
 78 | commonplace	everyday	0
 79 | dedicated	devoted	0
 80 | inward	outward	1
 81 | reasonable	just	0
 82 | actual	imaginary	1
 83 | stout	robust	0
 84 | sturdy	hardy	0
 85 | descriptive	normative	1
 86 | real	royal	0
 87 | legitimate	invalid	1
 88 | atonal	tonal	1
 89 | chaste	virtuous	0
 90 | offensive	aggressive	0
 91 | satisfied	content	0
 92 | human	animal	1
 93 | red	reddish	0
 94 | much	little	1
 95 | flawless	flawed	1
 96 | reduced	subject	0
 97 | comprehensible	incomprehensible	1
 98 | biennial	annual	1
 99 | luminous	bright	0
100 | hypnotic	narcotic	0
101 | marine	terrestrial	1
102 | unreasonable	reasonable	1
103 | amusing	light	0
104 | poignant	painful	0
105 | square	solid	0
106 | heavenly	earthly	1
107 | unskillful	skillful	1
108 | sloping	vertical	1
109 | fantastic	terrific	0
110 | sentimental	emotional	0
111 | red	neutral	1
112 | ovate	elliptical	0
113 | true	accurate	0
114 | round	square	1
115 | mythical	real	1
116 | confident	timid	1
117 | romantic	fantastic	0
118 | less	more	1
119 | storied	famous	0
120 | pleased	displeased	1
121 | hearty	healthy	0
122 | evil	corrupt	0
123 | salty	saline	0
124 | first	earliest	0
125 | pulpy	soft	0
126 | gory	bloody	0
127 | bitter	painful	0
128 | funny	familiar	1
129 | complex	difficult	0
130 | discontinuous	continuous	1
131 | exogenous	endogenous	1
132 | illusionary	real	1
133 | amorous	romantic	0
134 | transparent	opaque	1
135 | unreliable	uncertain	0
136 | progressive	advanced	0
137 | analogous	like	0
138 | right	ripe	0
139 | separate	adjacent	1
140 | singular	plural	1
141 | female	male	1
142 | next	immediate	0
143 | sharp	steep	0
144 | social	antisocial	1
145 | stormy	calm	1
146 | rich	plain	1
147 | occasional	regular	1
148 | furious	enraged	0
149 | monophonic	polyphonic	1
150 | collective	distributive	1
151 | gross	nett	1
152 | turgid	bombastic	0
153 | absolute	pure	0
154 | lovely	enchanting	0
155 | noncancerous	cancerous	1
156 | indefinite	infinite	0
157 | light	gay	0
158 | extraneous	intrinsic	1
159 | childish	mature	1
160 | mad	angry	0
161 | aged	green	1
162 | logical	invalid	1
163 | rude	unrefined	0
164 | ready	convenient	0
165 | muscular	powerful	0
166 | fine	coarse	1
167 | divine	godly	0
168 | radical	moderate	1
169 | fortunate	unfortunate	1
170 | pickled	fresh	1
171 | secondary	subordinate	0
172 | opposite	same	1
173 | spiritual	pneumatic	0
174 | light	moderate	0
175 | magnetic	nonmagnetic	1
176 | independent	absolute	0
177 | mechanical	chemical	1
178 | weak	strong	1
179 | envious	jealous	0
180 | fake	genuine	1
181 | latent	actual	1
182 | inauspicious	auspicious	1
183 | dependable	safe	0
184 | unlikely	likely	1
185 | only	solitary	0
186 | affable	warm	0
187 | strict	close	0
188 | underground	open	1
189 | unimportant	great	1
190 | sluggish	slow	0
191 | nice	delicate	0
192 | incomparable	comparable	1
193 | contented	satisfied	0
194 | foggy	thick	0
195 | diploid	polyploid	1
196 | lawful	right	0
197 | delicate	lovely	0
198 | short	long	1
199 | lost	confused	0
200 | disjunct	conjunct	1
201 | specific	precise	0
202 | ecumenical	sectarian	1
203 | stark	powerful	0
204 | round	full	0
205 | unable	able	1
206 | extracellular	intracellular	1
207 | unoccupied	occupied	1
208 | centrifugal	centripetal	1
209 | open	evident	0
210 | expensive	inexpensive	1
211 | authentic	credible	0
212 | pretty	good	1
213 | clear	keen	0
214 | authoritarian	despotic	0
215 | bald	haired	1
216 | crazy	mad	0
217 | equivocal	univocal	1
218 | early	middle	1
219 | fresh	dirty	1
220 | dramatic	lyric	1
221 | anomalous	normal	1
222 | head	chief	0
223 | pilose	hairy	0
224 | arrogant	presumptuous	0
225 | natural	artificial	1
226 | open	private	1
227 | direct	express	0
228 | similar	unlike	1
229 | soft	loud	1
230 | lackadaisical	lazy	0
231 | glabrous	haired	1
232 | triclinic	monoclinic	1
233 | ineffective	strong	1
234 | transitory	ephemeral	0
235 | systemic	topical	1
236 | refined	tasteful	0
237 | loose	fine	1
238 | dumb	ridiculous	0
239 | correct	improper	1
240 | hefty	strong	0
241 | awake	unconscious	1
242 | distant	near	1
243 | shrewd	sharp	0
244 | native	aboriginal	0
245 | prostrate	erect	1
246 | slow	inactive	0
247 | intimate	remote	1
248 | provocative	exciting	0
249 | subtle	refined	0
250 | depressed	high	1
251 | overall	net	1
252 | unsure	confident	1
253 | weird	familiar	1
254 | eerie	spooky	0
255 | refined	graceful	0
256 | ruddy	red	0
257 | firm	soft	1
258 | good	benevolent	0
259 | basic	acidic	1
260 | awkward	inept	0
261 | naked	clothed	1
262 | likable	sympathetic	0
263 | ample	large	0
264 | sensual	mental	1
265 | metaphysical	empirical	1
266 | symmetrical	asymmetrical	1
267 | numerical	verbal	1
268 | maximum	maximal	0
269 | cutaneous	dermal	0
270 | young	undeveloped	0
271 | unintentional	unplanned	0
272 | strict	permissive	1
273 | secret	underground	0
274 | sad	satisfied	0
275 | systematic	taxonomic	0
276 | unidirectional	bidirectional	1
277 | unseeded	seeded	1
278 | distressing	good	1
279 | western	eastern	1
280 | free	destitute	0
281 | light	faint	0
282 | familiar	remote	1
283 | playful	serious	1
284 | monumental	monolithic	0
285 | eminent	high	0
286 | northerly	southerly	1
287 | polyunsaturated	saturated	1
288 | inhomogeneous	homogeneous	1
289 | frivolous	serious	1
290 | relevant	pertinent	0
291 | strict	lenient	1
292 | magnificent	majestic	0
293 | integral	perfect	0
294 | cheerful	sad	1
295 | successful	unsuccessful	1
296 | direct	relative	1
297 | desperate	hopeful	1
298 | subacid	sweet	1
299 | plump	thin	1
300 | general	vague	0
301 | terrestrial	epiphytic	1
302 | static	dynamic	1
303 | easy	poor	1
304 | small	superior	1
305 | yellow	healthy	1
306 | muscular	strong	0
307 | messy	chaotic	0
308 | new	unusual	0
309 | physical	mental	1
310 | intramural	extramural	1
311 | necessary	involuntary	0
312 | vague	shadowy	0
313 | large	prominent	0
314 | predicative	attributive	1
315 | hard	easy	1
316 | economic	unprofitable	1
317 | absolute	relative	1
318 | advantageous	disadvantageous	1
319 | rational	sound	0
320 | new	ancient	1
321 | magnetic	attractive	0
322 | active	quick	0
323 | overground	underground	1
324 | antique	ancient	0
325 | available	convenient	0
326 | national	private	1
327 | ugly	unpleasant	0
328 | coated	uncoated	1
329 | ethical	wrong	1
330 | familiar	conversant	0
331 | imperial	sovereign	0
332 | rich	lean	1
333 | harsh	disagreeable	0
334 | barbarous	brutal	0
335 | ethereal	real	1
336 | faulty	incorrect	0
337 | afferent	efferent	1
338 | square	circular	1
339 | radical	extreme	0
340 | liable	responsible	0
341 | gregarious	outgoing	0
342 | numerous	musical	0
343 | recurrent	persistent	0
344 | special	ordinary	1
345 | alien	native	1
346 | intuitive	logical	1
347 | reverse	forward	1
348 | bad	good	1
349 | huge	colossal	0
350 | careless	inattentive	0
351 | raw	hot	1
352 | unequal	equal	1
353 | elegant	classy	0
354 | net	final	0
355 | rocky	smooth	1
356 | exceptional	uncommon	0
357 | dull	clear	1
358 | desperate	safe	1
359 | sound	correct	0
360 | basic	canonical	0
361 | frustrated	disappointed	0
362 | absurd	logical	1
363 | disinterested	impartial	0
364 | dirty	obscene	0
365 | stillborn	alive	1
366 | regular	habitual	0
367 | buoyant	heavy	1
368 | ambiguous	double	0
369 | circular	rotary	0
370 | upbeat	downbeat	1
371 | vague	hazy	0
372 | celestial	earthly	1
373 | frugal	thrifty	0
374 | autotrophic	heterotrophic	1
375 | talented	untalented	1
376 | strange	wonderful	0
377 | romantic	practical	1
378 | greasy	oily	0
379 | candid	fair	0
380 | full	ample	0
381 | rainy	wet	0
382 | uninfected	infected	1
383 | relative	relevant	0
384 | central	cardinal	0
385 | communicable	incommunicable	1
386 | hungry	thirsty	0
387 | agrarian	urban	1
388 | white	clean	0
389 | reusable	expendable	1
390 | tremendous	small	1
391 | quiet	mild	0
392 | global	worldwide	0
393 | light	clean	0
394 | risky	safe	1
395 | large	liberal	0
396 | inconsistent	consistent	1
397 | contrary	adverse	0
398 | desperate	depressed	0
399 | 


--------------------------------------------------------------------------------
/dataset/noun-pairs.test:
--------------------------------------------------------------------------------
   1 | goliath	giant	0
   2 | quality	sort	0
   3 | cover	screening	0
   4 | efficacy	effectiveness	0
   5 | cause	ground	0
   6 | kid	parent	1
   7 | domestic	foreign	1
   8 | specific	generic	1
   9 | subject	case	0
  10 | guilt	innocence	1
  11 | sterility	fertility	1
  12 | vegetable	mineral	1
  13 | hostel	inn	0
  14 | cocaine	girl	0
  15 | mercury	spirit	0
  16 | legitimacy	illegitimacy	1
  17 | conjunct	disjunct	1
  18 | conspiracy	disagreement	1
  19 | helm	director	0
  20 | smack	slap	0
  21 | soft	hard	1
  22 | aversion	distaste	0
  23 | fore	aft	1
  24 | grandmother	grandson	1
  25 | hunter	forager	0
  26 | degeneracy	corruption	0
  27 | foot	plan	0
  28 | sundown	sunup	1
  29 | pest	nuisance	0
  30 | hope	despair	1
  31 | paperback	hardcover	1
  32 | scripture	document	0
  33 | gentry	aristocracy	0
  34 | womanhood	woman	0
  35 | highlander	lowlander	1
  36 | minister	parson	0
  37 | breathing	stop	0
  38 | person	body	0
  39 | breed	crossbreed	0
  40 | bolt	dart	0
  41 | wane	wax	1
  42 | binary	ascii	1
  43 | daughter	boy	1
  44 | theism	pantheism	1
  45 | plain	gorge	1
  46 | remoteness	closeness	1
  47 | underestimate	overestimate	1
  48 | configuration	figure	0
  49 | order	decree	0
  50 | matter	form	1
  51 | champion	hero	0
  52 | mouth	lip	0
  53 | balance	unbalance	1
  54 | believer	worshipper	0
  55 | jerk	press	1
  56 | midwife	obstetrician	0
  57 | poll	strip	0
  58 | poet	troubadour	0
  59 | laundry	washing	0
  60 | health	illness	1
  61 | girl	boy	1
  62 | daybreak	sunset	1
  63 | dissipation	diffusion	0
  64 | deceleration	acceleration	1
  65 | prefix	affix	0
  66 | fault	faulting	0
  67 | downhill	uphill	1
  68 | hood	cowl	0
  69 | placebo	nocebo	1
  70 | cladode	phylloclade	0
  71 | race	running	0
  72 | design	create	0
  73 | room	seat	0
  74 | deficit	lead	1
  75 | ancestor	antecedent	0
  76 | phase	state	0
  77 | daytime	nighttime	1
  78 | pass	head	0
  79 | glory	pride	0
  80 | detriment	benefit	1
  81 | disassociation	association	1
  82 | patient	impatient	1
  83 | undergraduate	graduate	1
  84 | internal	external	1
  85 | black	white	1
  86 | cornflour	cornstarch	0
  87 | goblin	demon	0
  88 | microbe	microorganism	0
  89 | dwelling	cottage	0
  90 | score	record	0
  91 | lowness	highness	1
  92 | endurance	suffering	0
  93 | stack	pile	1
  94 | devil	god	1
  95 | boulevard	road	0
  96 | beginning	ending	1
  97 | origin	beginning	0
  98 | brown	bistre	0
  99 | density	dispersion	1
 100 | aunt	nephew	1
 101 | infielder	outfielder	1
 102 | infantry	cavalry	1
 103 | satan	adversary	0
 104 | gesture	posture	0
 105 | prostitution	degradation	0
 106 | new	ancient	1
 107 | party	person	0
 108 | correspondence	symmetry	0
 109 | acquittal	sentence	1
 110 | reflection	reflectivity	0
 111 | truth	nonsense	1
 112 | intestine	chitterlings	0
 113 | separation	union	1
 114 | misbehavior	behavior	0
 115 | transparency	opacity	1
 116 | rigidity	flexibility	1
 117 | regent	ruler	0
 118 | organization	association	0
 119 | sink	decrease	0
 120 | roll	collar	0
 121 | climb	descent	1
 122 | epicenter	hypocenter	1
 123 | liability	asset	1
 124 | toboggan	sledge	0
 125 | weaponry	munition	0
 126 | emptiness	fullness	1
 127 | autonomy	heteronomy	1
 128 | microcosm	macrocosm	1
 129 | height	stature	0
 130 | employee	man	0
 131 | brethren	sister	1
 132 | waiter	attendant	0
 133 | law	gospel	1
 134 | swan	cygnet	0
 135 | antecedent	descendant	1
 136 | weakening	strengthening	1
 137 | valency	degree	0
 138 | cut	steak	0
 139 | convent	monastery	0
 140 | twist	device	0
 141 | palimony	alimony	1
 142 | shout	whisper	1
 143 | bag	pocket	0
 144 | functionality	service	0
 145 | runner	stolon	0
 146 | approbation	condemnation	1
 147 | rationalism	traditionalism	1
 148 | doctrine	teaching	0
 149 | dissimilation	assimilation	1
 150 | gardener	nurseryman	0
 151 | black	descent	0
 152 | designer	decorator	0
 153 | distress	anxiety	0
 154 | pathos	ethos	1
 155 | candle	paschal	0
 156 | belief	unbelief	1
 157 | descendant	ancestor	1
 158 | house	hovel	0
 159 | pessimist	optimist	1
 160 | milk	buttermilk	0
 161 | aunty	aunt	0
 162 | nobody	everybody	1
 163 | distribution	density	1
 164 | neighborhood	region	0
 165 | strainer	filter	0
 166 | posting	bill	0
 167 | serbia	srbija	0
 168 | poison	virus	0
 169 | pleasantness	unpleasantness	1
 170 | downtime	uptime	1
 171 | caryopsis	grain	0
 172 | orthodoxy	heresy	1
 173 | excavation	tunnel	1
 174 | shaft	beam	0
 175 | roman	italic	1
 176 | banner	streamer	0
 177 | crew	member	0
 178 | antonym	synonym	1
 179 | transition	passing	0
 180 | past	future	1
 181 | grape	niagara	0
 182 | lord	overlord	0
 183 | source	beginning	0
 184 | cubicle	stall	0
 185 | pressure	insistence	0
 186 | balloon	toy	0
 187 | oracle	seer	0
 188 | engagement	mesh	0
 189 | hollow	hill	1
 190 | obscurity	fame	1
 191 | cold	heat	1
 192 | inflation	deflation	1
 193 | top	base	1
 194 | friend	stranger	1
 195 | throat	windpipe	0
 196 | fame	church	0
 197 | demeanor	conduct	0
 198 | ebb	flood	1
 199 | marketer	vendor	0
 200 | office	post	0
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 968 | wand	sceptre	0
 969 | bag	purse	0
 970 | rightness	wrongness	1
 971 | polarisation	polarization	0
 972 | strength	stress	0
 973 | category	tribe	0
 974 | sunset	sunrise	1
 975 | miosis	mydriasis	1
 976 | salesman	saleswoman	1
 977 | bane	boon	1
 978 | two	deuce	0
 979 | immunity	susceptibility	1
 980 | stay	hold	0
 981 | dish	beauty	0
 982 | loaf	block	0
 983 | decriminalization	criminalization	1
 984 | match	couple	0
 985 | opponent	supporter	1
 986 | rope	sheet	0
 987 | crescendo	decrescendo	1
 988 | trail	draw	0
 989 | correctness	incorrectness	1
 990 | valley	peak	1
 991 | dysphoria	euphoria	1
 992 | lands	land	0
 993 | rapture	bliss	0
 994 | hawk	dove	1
 995 | list	listing	0
 996 | failure	deterioration	0
 997 | degeneration	regeneration	1
 998 | diamagnetism	paramagnetism	1
 999 | plateau	valley	1
1000 | tissue	membrane	0
1001 | diminuendo	crescendo	1
1002 | secrecy	secret	0
1003 | gang	squad	0
1004 | white	cracker	0
1005 | adjective	substantive	1
1006 | remainder	end	0
1007 | distribution	concentration	1
1008 | nonmember	member	1
1009 | low	hill	0
1010 | consonant	labial	0
1011 | chapel	chantry	0
1012 | rising	fall	1
1013 | railroad	rail	0
1014 | buck	single	0
1015 | wartime	peacetime	1
1016 | nothing	everything	1
1017 | lord	husband	0
1018 | melanism	albinism	1
1019 | understudy	standby	0
1020 | services	good	1
1021 | 


--------------------------------------------------------------------------------
/dataset/noun-pairs.val:
--------------------------------------------------------------------------------
  1 | collateral	security	0
  2 | literacy	illiteracy	1
  3 | vortex	eddy	0
  4 | domain	codomain	1
  5 | skin	cutis	0
  6 | buckle	bow	0
  7 | sorrow	joy	1
  8 | union	pairing	0
  9 | prairie	forest	1
 10 | preparation	training	0
 11 | starter	crank	0
 12 | play	gaming	0
 13 | countenance	aid	0
 14 | catalyst	inhibitor	1
 15 | honesty	goodness	0
 16 | messenger	courier	0
 17 | rostrum	pulpit	0
 18 | apogee	perigee	1
 19 | valley	corrie	0
 20 | hardness	softness	1
 21 | monogamy	polygamy	1
 22 | sort	variety	0
 23 | strength	weakness	1
 24 | humour	comedy	0
 25 | row	sequence	0
 26 | reverence	irreverence	1
 27 | island	mainland	1
 28 | compact	agreement	0
 29 | joy	mirth	0
 30 | oogenesis	spermatogenesis	1
 31 | nearsightedness	farsightedness	1
 32 | slowness	clumsiness	0
 33 | resident	nonresident	1
 34 | center	essence	0
 35 | alien	citizen	1
 36 | layman	expert	1
 37 | end	beginning	1
 38 | intercourse	coitus	0
 39 | teletypewriter	teleprinter	0
 40 | series	chain	0
 41 | brine	seawater	0
 42 | love	hate	1
 43 | export	import	1
 44 | position	stead	0
 45 | disinflation	deflation	1
 46 | goodness	badness	1
 47 | arbitration	decision	0
 48 | cuckold	horn	0
 49 | wrongness	rightness	1
 50 | calendar	register	0
 51 | hardball	softball	1
 52 | offense	defence	1
 53 | possibility	impossibility	1
 54 | end	destruction	0
 55 | contest	competition	0
 56 | large	small	1
 57 | conduct	direction	0
 58 | nephew	uncle	1
 59 | touch	trace	0
 60 | hope	fear	1
 61 | woman	girl	1
 62 | descent	ascent	1
 63 | prosecution	denial	1
 64 | femaleness	maleness	1
 65 | privatization	nationalization	1
 66 | proof	test	0
 67 | adsorption	desorption	1
 68 | affinity	consanguinity	1
 69 | blow	punch	0
 70 | gain	loss	1
 71 | disloyalty	loyalty	1
 72 | new	old	1
 73 | convexity	concavity	1
 74 | conclusion	beginning	1
 75 | list	bill	0
 76 | chinese	meal	0
 77 | commencement	end	1
 78 | overgrowth	undergrowth	1
 79 | trench	dike	1
 80 | appreciation	depreciation	1
 81 | fact	actuality	0
 82 | medulla	cortex	1
 83 | mark	characteristic	0
 84 | compassion	empathy	0
 85 | eyes	center	0
 86 | anticline	syncline	1
 87 | inability	ability	1
 88 | residence	abode	0
 89 | gown	frock	0
 90 | dramatics	theater	0
 91 | disguise	mask	0
 92 | shadow	ghost	0
 93 | motion	rest	1
 94 | guard	care	0
 95 | praise	condemnation	1
 96 | worshipper	believer	0
 97 | good	benefit	0
 98 | unification	separation	1
 99 | lodge	hut	0
100 | northeast	southwest	1
101 | charge	duty	0
102 | framing	frame	0
103 | aphelion	perihelion	1
104 | cut	track	0
105 | shooter	firearm	0
106 | center	midpoint	0
107 | end	middle	1
108 | amateur	professional	1
109 | rest	motion	1
110 | paralysis	paraplegia	0
111 | polygamy	monogamy	1
112 | broadsheet	tabloid	1
113 | giant	heavyweight	0
114 | joint	junction	0
115 | banknote	note	0
116 | significance	meaning	0
117 | micron	micrometre	0
118 | operation	agency	0
119 | trade	custom	0
120 | man	civilian	1
121 | bawd	whore	0
122 | pride	humility	1
123 | barrel	drum	1
124 | relevance	irrelevance	1
125 | turn	twist	0
126 | nobody	everyone	1
127 | nothing	something	1
128 | uncle	nephew	1
129 | epinephrine	adrenalin	0
130 | sickness	health	1
131 | crescendo	diminuendo	1
132 | dose	pill	0
133 | moonset	moonrise	1
134 | curl	extension	1
135 | endoparasite	ectoparasite	1
136 | distance	interval	1
137 | wisdom	foolishness	1
138 | maintenance	continuation	0
139 | drive	hole	0
140 | newsprint	newspaper	0
141 | friend	enemy	1
142 | futures	past	1
143 | auditorium	orchestra	0
144 | gas	petrol	0
145 | parent	daughter	1
146 | cinder	clinker	0
147 | public	inn	0
148 | earliness	lateness	1
149 | disadvantage	drawback	0
150 | eye	middle	0
151 | producer	form	0
152 | innovation	invention	0
153 | end	remainder	0
154 | aunty	uncle	1
155 | middle	first	1
156 | mode	custom	0
157 | unveiling	debut	0
158 | devil	angel	1
159 | index	power	0
160 | starboard	port	1
161 | antagonist	protagonist	1
162 | note	tone	0
163 | documentary	fiction	1
164 | interrogation	answer	1
165 | auntie	uncle	1
166 | polygyny	polyandry	1
167 | oxidation	reduction	1
168 | narrator	teller	0
169 | start	stop	1
170 | destruction	annihilation	0
171 | proponent	detractor	1
172 | protocol	procedure	0
173 | fold	boundary	0
174 | profession	declaration	0
175 | dislike	liking	1
176 | tail	arse	0
177 | professional	amateur	1
178 | mainland	peninsula	1
179 | layman	priest	1
180 | bad	good	1
181 | chemise	shift	0
182 | plain	vale	1
183 | lowbrow	highbrow	1
184 | surplus	deficit	1
185 | caress	kiss	0
186 | conduct	construction	0
187 | wife	husband	1
188 | light	dark	1
189 | tablet	pad	0
190 | crime	robbery	0
191 | consistory	court	0
192 | vegetable	animal	1
193 | peer	noble	0
194 | forest	wood	0
195 | connection	disconnection	1
196 | fleck	dot	0
197 | indentation	inlet	0
198 | proxy	agent	0
199 | immortal	mortal	1
200 | sound	chime	0
201 | hundred	century	0
202 | watermill	windmill	1
203 | war	peace	1
204 | openness	closeness	1
205 | run	running	0
206 | witwatersrand	reef	0
207 | 


--------------------------------------------------------------------------------
/dataset/verb-pairs.test:
--------------------------------------------------------------------------------
  1 | act	refrain	1
  2 | discontinue	keep	1
  3 | beam	radiate	0
  4 | inscribe	impress	0
  5 | loosen	tighten	1
  6 | tender	demand	1
  7 | leave	come	1
  8 | incapacitate	enable	1
  9 | possess	affect	0
 10 | hate	love	1
 11 | diffuse	penetrate	0
 12 | ruin	sink	0
 13 | disagree	match	1
 14 | qualify	disqualify	1
 15 | repulse	draw	1
 16 | resent	wish	1
 17 | discontinue	proceed	1
 18 | fill	empty	1
 19 | back	advance	1
 20 | market	commercialize	0
 21 | brave	mean	1
 22 | eliminate	necessitate	1
 23 | endanger	jeopardize	0
 24 | abstain	take	1
 25 | file	rank	1
 26 | head	tail	1
 27 | let	prohibit	1
 28 | stop	uphold	1
 29 | despise	ignore	0
 30 | recede	withdraw	0
 31 | tread	rise	1
 32 | laugh	weep	1
 33 | gestate	conceive	0
 34 | devise	say	0
 35 | commence	cease	1
 36 | cancel	scrub	0
 37 | unite	merge	0
 38 | discontinue	continue	1
 39 | lend	add	0
 40 | demote	promote	1
 41 | raise	parent	0
 42 | praise	criticise	1
 43 | mix	segregate	1
 44 | detest	love	1
 45 | let	rent	0
 46 | cherish	promote	0
 47 | donate	present	0
 48 | head	point	1
 49 | need	obviate	1
 50 | hold	continue	0
 51 | force	push	1
 52 | sight	see	0
 53 | outlaw	legalise	1
 54 | differentiate	integrate	1
 55 | upgrade	relegate	1
 56 | trust	distrust	1
 57 | trim	adorn	0
 58 | embrace	cherish	0
 59 | unite	split	1
 60 | dispute	struggle	0
 61 | murder	remove	0
 62 | dirty	clean	1
 63 | bury	pit	0
 64 | model	design	0
 65 | owe	own	0
 66 | wield	manipulate	0
 67 | trim	shave	0
 68 | enter	inscribe	0
 69 | hire	lease	0
 70 | ostracize	exclude	0
 71 | distribute	circulate	0
 72 | scatter	meet	1
 73 | chain	bind	0
 74 | convene	separate	1
 75 | dog	pursue	0
 76 | prompt	advise	0
 77 | assure	ascertain	0
 78 | possess	gain	0
 79 | overpay	underpay	1
 80 | track	monitor	0
 81 | divulge	break	0
 82 | achieve	reach	0
 83 | underpay	overpay	1
 84 | ascertain	find	0
 85 | consist	rake	0
 86 | level	demolish	0
 87 | work	cultivate	0
 88 | strip	loot	0
 89 | multiply	divide	1
 90 | repel	appeal	1
 91 | specify	condition	0
 92 | fasten	unfasten	1
 93 | elaborate	reduce	1
 94 | starve	feed	1
 95 | vanish	appear	1
 96 | suppress	overwhelm	0
 97 | conquer	rout	0
 98 | deprive	present	1
 99 | injure	praise	1
100 | slow	hinder	0
101 | pull	pluck	0
102 | smash	wreck	0
103 | return	fall	0
104 | stuff	empty	1
105 | overpower	overcome	0
106 | exacerbate	ameliorate	1
107 | anneal	toughen	0
108 | suspect	rely	1
109 | build	demolish	1
110 | hang	plan	0
111 | ridicule	lampoon	0
112 | disown	leave	1
113 | flick	click	0
114 | disregard	attend	1
115 | catch	drop	1
116 | research	search	0
117 | accept	decline	1
118 | foreclose	bar	0
119 | hiss	clap	1
120 | feminize	masculinize	1
121 | warp	buckle	0
122 | brag	boast	0
123 | erect	raze	1
124 | fix	break	1
125 | break	restore	1
126 | cease	preserve	1
127 | generate	die	1
128 | single	retire	0
129 | think	block	1
130 | burn	scald	0
131 | vote	doom	0
132 | sight	show	0
133 | take	postulate	0
134 | broaden	specialize	1
135 | sniff	suspect	0
136 | disprove	confirm	1
137 | form	shape	0
138 | highlight	downplay	1
139 | prevent	cause	1
140 | mind	forget	1
141 | bear	entertain	0
142 | depart	perish	0
143 | centralize	decentralize	1
144 | encircle	surround	0
145 | outlaw	legalize	1
146 | blame	free	1
147 | substantiate	prove	0
148 | push	draw	1
149 | measure	evaluate	0
150 | waste	conserve	1
151 | emit	absorb	1
152 | tip	tap	0
153 | unite	divide	1
154 | zip	unzip	1
155 | bring	import	0
156 | further	aid	0
157 | assign	appoint	0
158 | boost	push	0
159 | have	desist	1
160 | miss	attend	1
161 | promote	denigrate	1
162 | pay	default	1
163 | abandon	keep	1
164 | overestimate	underestimate	1
165 | qualify	limit	0
166 | deny	refuse	0
167 | desire	wish	0
168 | decrease	rise	1
169 | hold	last	0
170 | abide	tolerate	0
171 | influence	tempt	0
172 | fire	employ	1
173 | allow	appropriate	0
174 | divide	unite	1
175 | pay	punish	0
176 | misbehave	behave	1
177 | blame	excuse	1
178 | concur	differ	1
179 | abandon	continue	1
180 | marry	couple	0
181 | play	frolic	0
182 | leap	cover	0
183 | decline	ameliorate	1
184 | share	enter	0
185 | move	induce	0
186 | prospect	face	0
187 | mention	enumerate	0
188 | disagree	fit	1
189 | include	except	1
190 | add	tally	0
191 | decipher	encode	1
192 | minimise	magnify	1
193 | lecture	reprimand	0
194 | west	east	1
195 | retire	rise	1
196 | deal	bargain	0
197 | annul	repeal	0
198 | aestivate	hibernate	1
199 | fix	engrave	0
200 | apprehend	understand	0
201 | advance	retreat	1
202 | regard	remark	0
203 | refuse	take	1
204 | satisfy	disappoint	1
205 | tell	evidence	0
206 | lighten	light	0
207 | temper	manage	0
208 | pass	die	0
209 | narrow	widen	1
210 | mark	ignore	1
211 | improve	refute	0
212 | hire	terminate	1
213 | deposit	draw	1
214 | recover	regain	0
215 | recover	find	0
216 | bring	convey	0
217 | light	extinguish	1
218 | block	think	1
219 | unmake	make	1
220 | permit	keep	1
221 | drive	draw	1
222 | weaken	intensify	1
223 | collect	muster	0
224 | ascend	fall	1
225 | concave	convex	1
226 | affect	overcome	0
227 | mold	fashion	0
228 | enfranchise	disfranchise	1
229 | trust	hope	0
230 | pack	unpack	1
231 | convex	concave	1
232 | infringe	contravene	0
233 | interpret	decipher	0
234 | fall	settle	0
235 | give	starve	1
236 | contradict	support	1
237 | ambush	lurk	0
238 | supply	furnish	0
239 | roll	range	0
240 | fit	disagree	1
241 | increase	cut	1
242 | mature	grow	0
243 | allude	point	0
244 | approach	avoid	1
245 | ease	facilitate	0
246 | let	prevent	1
247 | square	adjust	0
248 | deport	repatriate	1
249 | open	fold	1
250 | separate	sort	0
251 | wait	observe	0
252 | contradict	confirm	1
253 | show	read	0
254 | start	end	1
255 | comment	observe	0
256 | approve	commend	0
257 | refuse	admit	1
258 | praise	condemn	1
259 | have	deliver	0
260 | weaken	escalate	1
261 | garner	earn	0
262 | recover	deteriorate	1
263 | believe	disbelieve	1
264 | finish	close	0
265 | pillage	strip	0
266 | draw	withdraw	0
267 | privilege	claim	0
268 | lose	keep	1
269 | lose	gain	1
270 | spread	fold	1
271 | partake	share	0
272 | tie	draw	0
273 | desist	continue	1
274 | yield	stand	1
275 | check	restrain	0
276 | begin	terminate	1
277 | lapse	pass	0
278 | command	dominate	0
279 | claim	disclaim	1
280 | dress	garb	0
281 | omit	mention	1
282 | reason	think	0
283 | reduce	magnify	1
284 | disappoint	fail	0
285 | adorn	deck	0
286 | praise	abuse	1
287 | ignore	watch	1
288 | total	tally	0
289 | clog	foul	0
290 | average	run	0
291 | range	classify	0
292 | bend	stoop	0
293 | contract	expand	1
294 | cook	make	0
295 | segregate	desegregate	1
296 | deposit	free	1
297 | start	cease	1
298 | steal	pinch	0
299 | blend	separate	1
300 | pressurize	depressurize	1
301 | take	eliminate	1
302 | stream	burn	0
303 | drive	motivate	0
304 | act	stir	0
305 | dissent	follow	1
306 | devastate	demolish	0
307 | lock	unlock	1
308 | refuse	consent	1
309 | ward	repel	0
310 | exclude	admit	1
311 | round	beat	0
312 | detain	rush	1
313 | gather	distribute	1
314 | declassify	classify	1
315 | clap	boo	1
316 | attain	accomplish	0
317 | bud	blossom	0
318 | heighten	raise	0
319 | discharge	exonerate	0
320 | trip	stumble	0
321 | point	orient	0
322 | break	elevate	1
323 | free	detain	1
324 | deregulate	regulate	1
325 | sew	run	0
326 | evaporate	solidify	1
327 | deflate	inflate	1
328 | droop	erect	1
329 | dissent	hold	1
330 | finish	begin	1
331 | abuse	deceive	0
332 | soften	harden	1
333 | appropriate	earmark	0
334 | predecease	outlive	1
335 | gain	reduce	1
336 | uphold	discontinue	1
337 | freeze	unfreeze	1
338 | contrive	devise	0
339 | convey	fetch	0
340 | arise	retire	1
341 | allow	prohibit	1
342 | demonstrate	certify	0
343 | insure	see	0
344 | model	plan	0
345 | brown	toast	0
346 | undershoot	overshoot	1
347 | mistrust	trust	1
348 | hamper	hinder	0
349 | obviate	require	1
350 | obey	defy	1
351 | stand	kneel	1
352 | match	touch	0
353 | pitch	shift	0
354 | venture	assume	0
355 | force	ram	0
356 | describe	class	0
357 | describe	distinguish	0
358 | nullify	create	1
359 | circumnavigate	round	0
360 | discontinue	preserve	1
361 | study	analyse	0
362 | inflate	deflate	1
363 | envisage	regard	0
364 | differ	equal	1
365 | downplay	magnify	1
366 | rehabilitate	purge	1
367 | comprise	encircle	0
368 | favor	privilege	0
369 | draw	deposit	1
370 | run	discuss	0
371 | invest	seat	0
372 | diverge	meet	1
373 | uphold	stop	1
374 | warn	caution	0
375 | begin	commence	0
376 | end	scrap	0
377 | liquefy	solidify	1
378 | synchronize	desynchronize	1
379 | garner	spread	1
380 | dissuade	persuade	1
381 | supplant	supersede	0
382 | underplay	overplay	1
383 | advance	lose	1
384 | credit	debit	1
385 | creep	sneak	0
386 | borrow	lend	1
387 | comment	notice	0
388 | blink	flash	0
389 | employ	can	1
390 | underpin	support	0
391 | coin	strike	0
392 | fail	manage	1
393 | call	invite	0
394 | rid	clear	0
395 | miss	feature	1
396 | condemn	save	1
397 | rap	tap	0
398 | attack	defend	1
399 | fix	number	0
400 | tally	total	0
401 | stick	move	1
402 | show	hide	1
403 | place	divest	1
404 | hire	displace	1
405 | lose	come	1
406 | ignore	attend	1
407 | express	represent	0
408 | raise	dismantle	1
409 | leave	enter	1
410 | forget	learn	1
411 | mention	recount	0
412 | induce	stimulate	0
413 | wear	freshen	1
414 | stay	move	1
415 | cease	start	1
416 | disorganize	organize	1
417 | order	disorder	1
418 | cooperate	contend	1
419 | soften	sharpen	1
420 | have	decline	1
421 | appreciate	depreciate	1
422 | praise	knock	1
423 | desire	burn	0
424 | scatter	collect	1
425 | intend	intensify	0
426 | foreclose	stop	0
427 | suffer	get	0
428 | annul	destroy	0
429 | answer	reply	0
430 | reproach	condemn	0
431 | master	overcome	0
432 | weigh	balance	0
433 | clean	soil	1
434 | predicate	state	0
435 | assign	apportion	0
436 | dispose	apply	0
437 | perceive	miss	1
438 | score	charge	0
439 | leave	arrive	1
440 | improve	decline	1
441 | improve	aggravate	1
442 | naturalise	cultivate	0
443 | look	back	1
444 | stay	change	1
445 | reduce	oxidize	1
446 | unfurl	furl	1
447 | lay	sit	1
448 | rise	appear	0
449 | hypothesize	theorize	0
450 | manage	fail	1
451 | forget	remember	1
452 | suit	agree	0
453 | stick	free	1
454 | match	disagree	1
455 | mount	dismount	1
456 | stand	lie	1
457 | expand	shrink	1
458 | maximise	minimise	1
459 | drown	overpower	0
460 | walk	ride	1
461 | hold	harbor	0
462 | waive	claim	1
463 | hold	dissent	1
464 | encode	decrypt	1
465 | skipper	captain	0
466 | defuse	fuse	1
467 | form	create	0
468 | observe	disrespect	1
469 | arise	fall	1
470 | see	encounter	0
471 | sprout	germinate	0
472 | eat	bother	0
473 | connect	detach	1
474 | advance	demote	1
475 | protect	ruin	1
476 | aim	propose	0
477 | try	experience	0
478 | import	export	1
479 | round	finish	0
480 | purchase	sell	1
481 | undock	dock	1
482 | emphasize	disregard	1
483 | puff	draw	0
484 | house	shop	0
485 | hitch	unhitch	1
486 | dress	undress	1
487 | accomplish	perform	0
488 | focus	scatter	1
489 | assemble	meet	0
490 | besiege	invest	0
491 | include	end	0
492 | dare	venture	0
493 | mention	ignore	1
494 | cajole	coax	0
495 | tilt	lean	0
496 | frighten	entice	1
497 | operate	function	0
498 | announce	make	0
499 | breach	keep	1
500 | think	guess	0
501 | terminate	hire	1
502 | wave	float	0
503 | temper	agree	0
504 | doubt	trust	1
505 | beat	drum	0
506 | jam	free	1
507 | pause	break	0
508 | differentiate	dedifferentiate	1
509 | enlarge	cut	1
510 | contradict	question	0
511 | elucidate	explain	0
512 | reduce	subject	0
513 | record	erase	1
514 | tempt	lure	0
515 | rise	descend	1
516 | defy	dare	0
517 | hang	show	0
518 | oxidise	reduce	1
519 | insert	withdraw	1
520 | pinch	bite	0
521 | lapse	fall	0
522 | fill	discharge	1
523 | paste	present	1
524 | carry	express	0
525 | have	abstain	1
526 | retreat	progress	1
527 | creep	crawl	0
528 | connect	disconnect	1
529 | uncover	cover	1
530 | throw	make	0
531 | marry	tie	0
532 | change	continue	1
533 | forestall	preclude	0
534 | forego	follow	1
535 | advise	apprise	0
536 | uncoil	coil	1
537 | drive	constrain	0
538 | beg	give	1
539 | exhaust	discharge	0
540 | promote	oppose	1
541 | draw	repulse	1
542 | litter	trash	0
543 | estimate	appraise	0
544 | relate	describe	0
545 | handle	brake	0
546 | predecease	survive	1
547 | fail	bomb	0
548 | indicate	contraindicate	1
549 | preserve	keep	0
550 | sit	situate	0
551 | prevent	keep	0
552 | induct	introduce	0
553 | kick	foot	0
554 | accumulate	garner	0
555 | experience	time	0
556 | conform	vary	1
557 | dismiss	discount	0
558 | disinherit	bequeath	1
559 | increase	relax	1
560 | set	embarrass	0
561 | sack	devastate	0
562 | watch	guard	0
563 | mend	break	1
564 | parallel	like	0
565 | roll	unroll	1
566 | support	negate	1
567 | portray	depict	0
568 | break	hold	1
569 | run	indicate	0
570 | centre	concentrate	0
571 | draw	lengthen	0
572 | implode	explode	1
573 | chill	heat	1
574 | charge	calm	1
575 | promote	relegate	1
576 | concentrate	centre	0
577 | establish	abolish	1
578 | preach	evangelize	0
579 | type	sign	0
580 | gather	spread	1
581 | begin	end	1
582 | shift	switch	0
583 | grant	deny	1
584 | activate	inactivate	1
585 | decrease	increase	1
586 | postpone	hasten	1
587 | convoke	dissolve	1
588 | pick	collect	0
589 | dispute	resist	0
590 | influence	power	0
591 | require	exact	0
592 | straighten	bend	1
593 | consume	refrain	1
594 | influence	bribe	0
595 | bitch	whine	0
596 | dwell	live	0
597 | record	delete	1
598 | draw	drive	1
599 | intensify	relax	1
600 | embellish	vary	0
601 | tally	score	0
602 | attain	overtake	0
603 | school	shoal	0
604 | profit	lose	1
605 | vindicate	assert	0
606 | dissent	concur	1
607 | favour	prefer	0
608 | take	give	1
609 | advance	break	1
610 | list	attend	0
611 | raise	bump	1
612 | adjust	skew	1
613 | alter	maintain	1
614 | encipher	decipher	1
615 | indicate	hide	1
616 | strip	dress	1
617 | braid	plait	0
618 | see	find	0
619 | contrive	design	0
620 | oppose	contradict	0
621 | generate	proliferate	0
622 | start	stop	1
623 | encourage	stimulate	0
624 | free	immobilize	1
625 | cope	contend	0
626 | install	establish	0
627 | synthesize	analyze	1
628 | arise	rebel	0
629 | arrest	obstruct	0
630 | underbid	overbid	1
631 | appeal	attract	0
632 | dismiss	engage	1
633 | baptise	baptize	0
634 | devalue	revalue	1
635 | distribute	gather	1
636 | forbear	act	1
637 | vary	conform	1
638 | transfer	sequester	0
639 | continue	stop	1
640 | confute	show	1
641 | revalue	devalue	1
642 | wave	flood	0
643 | break	expose	0
644 | fail	succeed	1
645 | help	avoid	0
646 | twist	untwist	1
647 | succumb	survive	1
648 | shrink	stretch	1
649 | stabilise	destabilise	1
650 | deface	destroy	0
651 | hide	cover	0
652 | bear	uphold	0
653 | distort	falsify	0
654 | offer	provide	0
655 | sob	laugh	1
656 | raise	promote	0
657 | immerse	submerge	0
658 | vanish	die	0
659 | stalk	sneak	1
660 | free	implement	1
661 | spread	garner	1
662 | allow	disallow	1
663 | relieve	apply	1
664 | increase	spurt	0
665 | raise	level	1
666 | strike	attain	0
667 | embark	disembark	1
668 | result	terminate	0
669 | blind	deceive	0
670 | show	disprove	1
671 | divest	commit	1
672 | make	manage	0
673 | survive	yield	1
674 | blunt	sharpen	1
675 | strike	slash	0
676 | rise	wane	1
677 | establish	disprove	1
678 | represent	typify	0
679 | pioneer	initiate	0
680 | present	paste	1
681 | possess	acquaint	0
682 | advance	back	1
683 | rest	change	1
684 | avail	help	0
685 | force	draw	1
686 | come	leave	1
687 | intimidate	assure	1
688 | shout	whisper	1
689 | return	regress	0
690 | unfold	evolve	0
691 | advance	retire	1
692 | layer	overlay	0
693 | direct	organise	0
694 | examine	discuss	0
695 | block	free	1
696 | can	employ	1
697 | repress	crush	0
698 | reduce	expand	1
699 | inactivate	activate	1
700 | impede	free	1
701 | progress	retire	1
702 | slow	quicken	1
703 | fix	prepare	0
704 | move	refrain	1
705 | release	relinquish	0
706 | override	pass	0
707 | ascertain	check	0
708 | engage	dismiss	1
709 | refrain	have	1
710 | authorize	forbid	1
711 | shelve	postpone	0
712 | despise	esteem	1
713 | rise	lift	0
714 | deify	exalt	0
715 | save	reserve	0
716 | make	manufacture	0
717 | mention	disregard	1
718 | educate	prepare	0
719 | unpack	pack	1
720 | flap	wave	0
721 | negotiate	treat	0
722 | boil	freeze	1
723 | export	import	1
724 | confide	trust	0
725 | pass	fail	1
726 | practise	exercise	0
727 | elevate	lower	1
728 | delete	omit	0
729 | split	unite	1
730 | embolden	encourage	0
731 | derive	draw	0
732 | fix	bust	1
733 | hold	control	0
734 | retail	sell	0
735 | open	dehisce	0
736 | interrupt	resume	1
737 | allow	nix	1
738 | rise	source	0
739 | notice	ignore	1
740 | issue	arise	0
741 | incur	avoid	1
742 | refuse	allow	1
743 | mobilize	demobilize	1
744 | bid	direct	0
745 | refrain	take	1
746 | dissent	allow	1
747 | join	associate	0
748 | dress	embellish	0
749 | upstream	downstream	1
750 | mention	omit	1
751 | spread	collect	1
752 | sack	hire	1
753 | mourn	rejoice	1
754 | address	lecture	0
755 | issue	close	0
756 | commute	change	0
757 | foot	walk	0
758 | take	obviate	1
759 | add	subtract	1
760 | leak	escape	0
761 | shorten	dilate	1
762 | age	rejuvenate	1
763 | increase	fall	1
764 | refuse	grant	1
765 | feed	flow	0
766 | thicken	thin	1
767 | arm	disarm	1
768 | cry	laugh	1
769 | array	dress	0
770 | spot	recognize	0
771 | corroborate	establish	0
772 | hold	differ	1
773 | demonstrate	march	0
774 | cite	summon	0
775 | thrust	push	0
776 | veto	permit	1
777 | swap	switch	0
778 | examine	analyze	0
779 | diversify	specialise	1
780 | indicate	depict	0
781 | litter	bear	0
782 | tie	restrain	0
783 | desire	list	0
784 | wane	wax	1
785 | progress	recede	1
786 | agree	differ	1
787 | enfranchise	disenfranchise	1
788 | reject	approve	1
789 | confuse	confound	0
790 | found	rule	0
791 | prevent	let	1
792 | insult	consider	1
793 | fight	press	0
794 | institute	commence	0
795 | turn	sour	0
796 | apply	relieve	1
797 | gift	donate	0
798 | interpret	elucidate	0
799 | overwhelm	submerge	0
800 | distribute	apportion	0
801 | rely	distrust	1
802 | pass	notch	0
803 | propose	intend	0
804 | startle	frighten	0
805 | propagate	produce	0
806 | support	assist	0
807 | dilate	reduce	1
808 | disinter	bury	1
809 | support	contradict	1
810 | tread	press	0
811 | fall	plummet	0
812 | precede	follow	1
813 | depict	read	0
814 | compose	soothe	0
815 | stray	err	0
816 | cheer	kick	1
817 | raise	raze	1
818 | correct	chastise	0
819 | continue	cover	0
820 | strike	punish	0
821 | question	interrogate	0
822 | warm	fight	0
823 | include	admit	0
824 | achieve	kill	0
825 | diminish	enlarge	1
826 | dry	water	1
827 | enrol	enter	0
828 | clear	bounce	1
829 | conceal	reveal	1
830 | number	reckon	0
831 | write	publish	0
832 | abolish	abrogate	0
833 | front	back	1
834 | undergo	underlie	0
835 | blur	sharpen	1
836 | underexpose	overexpose	1
837 | sharpen	dull	1
838 | confine	free	1
839 | wedge	force	0
840 | borrow	loan	1
841 | abolish	found	1
842 | hiss	applaud	1
843 | convene	dissolve	1
844 | detain	free	1
845 | discipline	drill	0
846 | narrate	recount	0
847 | dehumidify	humidify	1
848 | exhume	unearth	0
849 | empower	endow	0
850 | sort	suit	0
851 | converge	center	0
852 | cancel	abrogate	0
853 | engage	fire	1
854 | recover	drop	1
855 | receive	experience	0
856 | eliminate	require	1
857 | like	pet	1
858 | revive	recall	1
859 | win	recede	1
860 | dull	sharpen	1
861 | enjoy	endure	1
862 | shop	store	0
863 | raise	recruit	0
864 | originate	start	0
865 | venture	guess	0
866 | dash	shatter	0
867 | shun	ostracise	0
868 | discharge	empty	0
869 | raise	lower	1
870 | render	state	0
871 | site	locate	0
872 | name	distinguish	0
873 | bolt	unbolt	1
874 | screen	hide	0
875 | remember	block	1
876 | ignore	mark	1
877 | blow	hit	0
878 | decentralise	centralise	1
879 | calm	stimulate	1
880 | assent	agree	0
881 | situate	fix	0
882 | attain	strike	0
883 | distinguish	perceive	0
884 | extend	cross	0
885 | convict	exonerate	1
886 | desist	take	1
887 | accompany	follow	0
888 | advance	bump	1
889 | validate	avoid	1
890 | kill	break	0
891 | interdict	allow	1
892 | stimulate	sedate	1
893 | concede	surrender	0
894 | renovate	refurbish	0
895 | fetch	revive	0
896 | proscribe	permit	1
897 | ferment	turn	0
898 | abet	encourage	0
899 | obscure	clear	1
900 | cut	wound	0
901 | administer	deal	0
902 | engage	pursue	0
903 | permit	proscribe	1
904 | dissipate	spend	0
905 | bust	fix	1
906 | symbolize	agree	0
907 | desert	fail	0
908 | scar	mark	0
909 | 


--------------------------------------------------------------------------------
/dataset/verb-pairs.train:
--------------------------------------------------------------------------------
   1 | resurrect	revive	0
   2 | frustrate	hinder	0
   3 | dishonor	honor	1
   4 | enjoy	suffer	1
   5 | deny	acknowledge	1
   6 | injure	benefit	1
   7 | take	draw	0
   8 | wish	resent	1
   9 | inter	disinter	1
  10 | bear	assume	0
  11 | align	skew	1
  12 | destroy	repair	1
  13 | ignore	mention	1
  14 | know	recognise	0
  15 | break	soften	0
  16 | reward	honor	0
  17 | stow	hold	0
  18 | combine	unite	0
  19 | theorize	hypothesize	0
  20 | range	reach	0
  21 | ordain	enact	0
  22 | usher	show	0
  23 | adjudicate	judge	0
  24 | lose	acquire	1
  25 | feel	find	0
  26 | change	remain	1
  27 | dispose	order	0
  28 | quench	light	1
  29 | concur	dissent	1
  30 | stand	sustain	0
  31 | constrain	force	0
  32 | impoverish	enrich	1
  33 | act	execute	0
  34 | reduce	elaborate	1
  35 | undress	dress	1
  36 | kick	drive	0
  37 | laugh	cry	1
  38 | condone	excuse	0
  39 | hook	unhook	1
  40 | negate	support	1
  41 | ice	freeze	0
  42 | mark	denounce	0
  43 | found	abolish	1
  44 | precede	succeed	1
  45 | sit	rise	1
  46 | proscribe	prescribe	1
  47 | prohibit	let	1
  48 | vibrate	oscillate	0
  49 | dissent	agree	1
  50 | encounter	battle	0
  51 | discharge	convict	1
  52 | disallow	permit	1
  53 | sit	position	0
  54 | mingle	mix	0
  55 | have	reject	1
  56 | lie	arise	1
  57 | have	refrain	1
  58 | improve	impair	1
  59 | knock	tap	0
  60 | can	hire	1
  61 | contain	comprise	0
  62 | pinch	squeeze	0
  63 | reach	strain	0
  64 | operate	disengage	1
  65 | set	rise	1
  66 | enforce	impose	0
  67 | deal	hand	0
  68 | unite	separate	1
  69 | oppose	match	0
  70 | shorten	expand	1
  71 | withdraw	lock	1
  72 | prove	justify	0
  73 | button	unbutton	1
  74 | steal	slip	0
  75 | refrain	move	1
  76 | elevate	break	1
  77 | thank	bless	0
  78 | fail	pass	1
  79 | destabilize	stabilize	1
  80 | wane	rise	1
  81 | enrich	deprive	1
  82 | sway	rock	0
  83 | please	anger	1
  84 | jostle	push	0
  85 | take	desist	1
  86 | raze	erect	1
  87 | forge	form	0
  88 | find	supply	0
  89 | swim	sink	1
  90 | sting	burn	0
  91 | unfasten	fasten	1
  92 | regurgitate	vomit	0
  93 | get	fashion	0
  94 | enter	participate	0
  95 | target	point	0
  96 | chat	gossip	0
  97 | mold	forge	0
  98 | generalize	specify	1
  99 | feature	miss	1
 100 | miss	get	1
 101 | change	stay	1
 102 | recite	declaim	0
 103 | boo	clap	1
 104 | inflict	administer	0
 105 | disintegrate	crumble	0
 106 | ban	censor	0
 107 | show	prove	0
 108 | pocket	steal	0
 109 | clear	cloud	1
 110 | divest	place	1
 111 | check	disagree	1
 112 | rise	fall	1
 113 | mesh	operate	0
 114 | complete	perfect	0
 115 | dissociate	associate	1
 116 | acquit	convict	1
 117 | cloud	clear	1
 118 | miss	perceive	1
 119 | specialize	diversify	1
 120 | enrich	deplete	1
 121 | fuse	defuse	1
 122 | sanction	support	0
 123 | control	predominate	0
 124 | centralise	decentralise	1
 125 | raise	levy	0
 126 | assert	defend	0
 127 | close	open	1
 128 | subtract	add	1
 129 | bivouac	camp	0
 130 | disperse	gather	1
 131 | bar	stop	0
 132 | flourish	develop	0
 133 | lock	disengage	1
 134 | observe	breach	1
 135 | sew	rip	1
 136 | hire	pay	0
 137 | stick	get	0
 138 | unzip	zip	1
 139 | flatten	sharpen	1
 140 | prohibit	permit	1
 141 | massacre	slaughter	0
 142 | challenge	question	0
 143 | survey	follow	0
 144 | confirm	dispute	1
 145 | modify	moderate	0
 146 | reserve	retain	0
 147 | elevate	relegate	1
 148 | praise	ridicule	1
 149 | resist	surrender	1
 150 | discover	find	0
 151 | detect	observe	0
 152 | impair	damage	0
 153 | direct	maneuver	0
 154 | feed	starve	1
 155 | pack	carry	0
 156 | break	observe	1
 157 | calculate	figure	0
 158 | like	hate	1
 159 | draw	write	0
 160 | bless	damn	1
 161 | demand	question	0
 162 | freeze	boil	1
 163 | expand	factor	1
 164 | float	settle	1
 165 | downplay	exaggerate	1
 166 | thin	thicken	1
 167 | cause	keep	0
 168 | conspire	contend	1
 169 | drag	trail	0
 170 | manage	administer	0
 171 | disorder	order	1
 172 | cleave	separate	0
 173 | stop	begin	1
 174 | fall	ascend	1
 175 | produce	yield	0
 176 | dispose	discard	0
 177 | gain	recede	1
 178 | flip	switch	0
 179 | offend	please	1
 180 | relent	stand	1
 181 | exaggerate	minimize	1
 182 | yank	pull	0
 183 | converge	diverge	1
 184 | ravage	spoil	0
 185 | inhale	exhale	1
 186 | dislike	like	1
 187 | forget	acquire	1
 188 | perform	fulfill	0
 189 | regain	lose	1
 190 | elude	escape	0
 191 | wash	rinse	0
 192 | cement	break	1
 193 | intend	extend	0
 194 | slay	dispatch	0
 195 | alive	dead	1
 196 | allow	veto	1
 197 | accept	refuse	1
 198 | oppose	pit	0
 199 | exhibit	present	0
 200 | frighten	fear	0
 201 | sit	arise	1
 202 | approximate	approach	0
 203 | wish	bid	0
 204 | repatriate	exile	1
 205 | give	show	0
 206 | permit	disallow	1
 207 | shoot	charge	0
 208 | sweat	toil	0
 209 | word	state	0
 210 | restate	repeat	0
 211 | muster	rally	0
 212 | release	immobilize	1
 213 | descend	rise	1
 214 | disbelieve	believe	1
 215 | utilise	apply	0
 216 | designate	appoint	0
 217 | admonish	inform	0
 218 | wedge	free	1
 219 | announce	hide	1
 220 | hoard	hide	0
 221 | court	seek	0
 222 | deform	twist	0
 223 | tame	subdue	0
 224 | allude	indicate	0
 225 | open	close	1
 226 | find	lose	1
 227 | pay	hire	0
 228 | love	detest	1
 229 | accomplish	reach	0
 230 | cease	uphold	1
 231 | scatter	crowd	1
 232 | minimize	amplify	1
 233 | keep	violate	1
 234 | swim	settle	1
 235 | free	deposit	1
 236 | diverge	conform	1
 237 | lift	rise	0
 238 | stand	yield	1
 239 | inter	exhume	1
 240 | suffer	enjoy	1
 241 | prosper	succeed	0
 242 | revive	restore	1
 243 | exempt	implement	1
 244 | fund	supply	0
 245 | quit	stay	1
 246 | display	discover	0
 247 | meet	satisfy	0
 248 | key	identify	0
 249 | stretch	load	0
 250 | alarm	disturb	0
 251 | lodge	free	1
 252 | flash	flip	0
 253 | bid	offer	0
 254 | prove	disprove	1
 255 | put	pit	0
 256 | omit	include	1
 257 | improve	advance	0
 258 | disrespect	observe	1
 259 | beg	set	1
 260 | demonstrate	evidence	0
 261 | alter	fix	1
 262 | frighten	scare	0
 263 | encounter	attack	0
 264 | procrastinate	delay	0
 265 | sound	try	0
 266 | gather	amass	0
 267 | salvage	save	0
 268 | dethrone	enthrone	1
 269 | sample	try	0
 270 | withdraw	operate	1
 271 | grant	gift	0
 272 | express	denote	0
 273 | adjudge	hold	0
 274 | forget	recall	1
 275 | roll	scroll	0
 276 | support	cherish	0
 277 | shrink	expand	1
 278 | fight	push	0
 279 | prescribe	appoint	0
 280 | supersede	omit	0
 281 | believe	suppose	0
 282 | present	absent	1
 283 | break	mend	1
 284 | swear	suspect	1
 285 | organize	disorganize	1
 286 | skyrocket	plummet	1
 287 | disperse	convene	1
 288 | bond	bind	0
 289 | abandon	leave	0
 290 | swoon	lose	0
 291 | decline	take	1
 292 | consent	refuse	1
 293 | succeed	fail	1
 294 | show	conceal	1
 295 | stop	intercept	0
 296 | retrieve	block	1
 297 | free	confine	1
 298 | urge	cheer	0
 299 | increase	drop	1
 300 | blow	strike	0
 301 | keep	break	1
 302 | imply	express	1
 303 | necessitate	eliminate	1
 304 | dock	undock	1
 305 | approximate	draw	0
 306 | destroy	make	1
 307 | summon	convene	0
 308 | absolve	punish	1
 309 | observe	violate	1
 310 | approve	reject	1
 311 | name	make	0
 312 | like	abhor	1
 313 | scatter	accumulate	1
 314 | see	visualize	0
 315 | upgrade	demote	1
 316 | strip	clean	0
 317 | point	hint	0
 318 | praise	criticize	1
 319 | require	need	0
 320 | begin	reintroduce	0
 321 | dehumanize	humanize	1
 322 | smother	strangle	0
 323 | disregard	consider	1
 324 | disprove	demonstrate	1
 325 | block	retrieve	1
 326 | cope	handle	0
 327 | corrupt	purify	1
 328 | maximize	minimise	1
 329 | stretch	tighten	0
 330 | recognise	distinguish	0
 331 | recede	win	1
 332 | experiment	experience	0
 333 | plant	devise	0
 334 | corrode	consume	0
 335 | increase	lessen	1
 336 | upgrade	downgrade	1
 337 | growl	rumble	0
 338 | grant	accord	0
 339 | weigh	press	0
 340 | see	figure	0
 341 | post	set	0
 342 | refuse	apply	1
 343 | negate	confirm	1
 344 | tolerate	brook	0
 345 | relegate	raise	1
 346 | pin	unpin	1
 347 | exacerbate	improve	1
 348 | relegate	submit	0
 349 | verify	disprove	1
 350 | admit	exclude	1
 351 | indulge	abstain	1
 352 | diminish	cut	0
 353 | fix	nail	0
 354 | instal	install	0
 355 | confirm	disconfirm	1
 356 | torment	afflict	0
 357 | reprint	reissue	0
 358 | boo	applaud	1
 359 | dwarf	shrink	0
 360 | advance	recede	1
 361 | canonize	glorify	0
 362 | bestow	accord	0
 363 | dictate	suggest	0
 364 | recount	mention	0
 365 | retrieve	forget	1
 366 | trail	float	0
 367 | nationalise	denationalise	1
 368 | detach	attach	1
 369 | worry	assure	1
 370 | affirm	negate	1
 371 | dash	smash	0
 372 | justify	vindicate	0
 373 | pull	drive	1
 374 | lose	win	1
 375 | release	freeze	1
 376 | strike	fall	0
 377 | ignore	note	1
 378 | suggest	evoke	0
 379 | employ	use	0
 380 | harass	protect	1
 381 | sink	float	1
 382 | spoil	damage	0
 383 | come	depart	1
 384 | continue	discontinue	1
 385 | manage	handle	0
 386 | fall	increase	1
 387 | upgrade	break	1
 388 | drive	trip	0
 389 | flower	bloom	0
 390 | exclude	include	1
 391 | specify	qualify	0
 392 | like	dislike	1
 393 | wake	sleep	1
 394 | despise	respect	1
 395 | stumble	hit	0
 396 | inspire	expire	1
 397 | rise	set	1
 398 | descend	ascend	1
 399 | moderate	soften	0
 400 | document	power	0
 401 | provide	condition	0
 402 | watch	ignore	1
 403 | reject	sanction	1
 404 | matter	weigh	0
 405 | prepare	fit	0
 406 | worry	reassure	1
 407 | except	include	1
 408 | coil	fold	0
 409 | eliminate	involve	1
 410 | register	enroll	0
 411 | sustain	uphold	0
 412 | speak	say	0
 413 | love	despise	1
 414 | transfer	give	0
 415 | saddle	sell	0
 416 | decouple	couple	1
 417 | withdraw	remove	0
 418 | apply	exempt	1
 419 | trust	entrust	0
 420 | mutilate	maim	0
 421 | prevent	stop	0
 422 | identify	place	0
 423 | rise	prove	0
 424 | impair	decline	0
 425 | gag	suffocate	0
 426 | clear	convict	1
 427 | tip	lean	0
 428 | will	disinherit	1
 429 | ebb	surge	1
 430 | encourage	urge	0
 431 | revoke	withdraw	0
 432 | improve	exacerbate	1
 433 | unplug	connect	1
 434 | represent	depict	0
 435 | materialize	dematerialize	1
 436 | offer	tender	0
 437 | pump	breathe	0
 438 | make	break	1
 439 | allege	adduce	0
 440 | shed	slough	0
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1210 | heat	cool	1
1211 | hinder	thwart	0
1212 | proscribe	allow	1
1213 | apply	defy	1
1214 | deny	allow	1
1215 | terminate	engage	1
1216 | maintain	allege	0
1217 | recede	advance	1
1218 | leave	disinherit	1
1219 | arise	issue	0
1220 | recognise	greet	0
1221 | accuse	acquit	1
1222 | scatter	concentrate	1
1223 | deteriorate	improve	1
1224 | unseal	seal	1
1225 | roll	unwind	1
1226 | enter	dip	0
1227 | grow	expand	0
1228 | take	understand	0
1229 | scoot	shoot	0
1230 | wrap	wind	0
1231 | grow	shrink	1
1232 | prepare	load	0
1233 | break	repair	1
1234 | run	rise	1
1235 | forge	fabricate	0
1236 | displace	employ	1
1237 | reduce	gain	1
1238 | drive	make	0
1239 | found	lose	1
1240 | decline	improve	1
1241 | undo	solve	0
1242 | wonder	question	0
1243 | devolve	transfer	0
1244 | delay	rush	1
1245 | duck	evade	0
1246 | withstand	hold	0
1247 | serve	dish	0
1248 | authorize	license	0
1249 | retire	advance	1
1250 | exhume	inter	1
1251 | point	end	0
1252 | recuperate	drop	1
1253 | obey	disobey	1
1254 | notice	acknowledge	0
1255 | dispute	contradict	0
1256 | hold	release	1
1257 | overflow	overwhelm	0
1258 | feature	lack	1
1259 | keep	offend	1
1260 | assure	worry	1
1261 | absorb	ingest	0
1262 | claim	waive	1
1263 | end	start	1
1264 | relegate	promote	1
1265 | lie	sit	1
1266 | respect	disrespect	1
1267 | toy	play	0
1268 | sear	burn	0
1269 | grow	arise	0
1270 | violate	observe	1
1271 | worry	plague	0
1272 | tangle	trap	0
1273 | establish	base	0
1274 | disembark	ship	1
1275 | cast	decide	0
1276 | glitter	shine	0
1277 | lower	elevate	1
1278 | curse	damn	0
1279 | capture	catch	0
1280 | run	determine	0
1281 | impede	assist	1
1282 | disperse	distribute	0
1283 | offend	annoy	0
1284 | accept	understand	0
1285 | unmask	mask	1
1286 | realise	gain	0
1287 | see	ascertain	0
1288 | disengage	engage	1
1289 | wax	wane	1
1290 | kick	toe	0
1291 | disengage	operate	1
1292 | admit	reject	1
1293 | defend	assail	1
1294 | cross	spoil	0
1295 | dry	soak	1
1296 | carry	acquit	0
1297 | win	advance	0
1298 | lay	allege	0
1299 | intend	contemplate	0
1300 | disinfect	infect	1
1301 | mount	unmount	1
1302 | strengthen	establish	0
1303 | refill	replenish	0
1304 | focus	blur	1
1305 | drive	pull	1
1306 | disqualify	qualify	1
1307 | get	terminate	1
1308 | voice	command	0
1309 | destruct	destroy	0
1310 | rescue	save	0
1311 | note	mark	0
1312 | respond	answer	0
1313 | postdate	predate	1
1314 | cap	surpass	0
1315 | disappear	evaporate	0
1316 | appoint	constitute	0
1317 | eliminate	ignore	0
1318 | explode	implode	1
1319 | embellish	enrich	0
1320 | develop	disentangle	0
1321 | show	confute	1
1322 | erect	level	1
1323 | accrue	mature	0
1324 | desegregate	segregate	1
1325 | light	quench	1
1326 | generate	get	0
1327 | corrupt	reform	1
1328 | continue	quit	1
1329 | clothe	strip	1
1330 | operate	cause	0
1331 | disfranchise	enfranchise	1
1332 | distinguish	discriminate	0
1333 | lay	rest	0
1334 | injure	harm	0
1335 | flunk	pass	1
1336 | idle	work	1
1337 | laugh	sob	1
1338 | disclaim	claim	1
1339 | conclude	end	0
1340 | free	jam	1
1341 | offend	keep	1
1342 | repel	attract	1
1343 | transmute	change	0
1344 | unhook	hook	1
1345 | expire	die	0
1346 | anticipate	forestall	0
1347 | embark	invest	0
1348 | shorten	abbreviate	0
1349 | withstand	surrender	1
1350 | strengthen	weaken	1
1351 | advance	withdraw	1
1352 | scream	shout	0
1353 | say	saw	0
1354 | light	clear	0
1355 | sign	subscribe	0
1356 | quit	participate	1
1357 | encourage	cheer	0
1358 | curtail	restrict	0
1359 | increase	pay	0
1360 | absent	present	1
1361 | remark	observe	0
1362 | introduce	present	0
1363 | get	con	0
1364 | urge	crowd	0
1365 | disconnect	link	1
1366 | disagree	concur	1
1367 | fail	flunk	0
1368 | pull	repulse	1
1369 | unscrew	screw	1
1370 | wreck	save	1
1371 | minimise	exaggerate	1
1372 | subscribe	agree	0
1373 | raise	break	1
1374 | deny	admit	1
1375 | control	guide	0
1376 | cower	squat	0
1377 | protect	attack	1
1378 | impede	help	1
1379 | settle	swim	1
1380 | seem	appear	0
1381 | return	repay	0
1382 | border	surround	0
1383 | look	reckon	0
1384 | fume	smoke	0
1385 | yield	pay	0
1386 | speed	delay	1
1387 | concoct	invent	0
1388 | despise	honor	1
1389 | worsen	improve	1
1390 | lighten	darken	1
1391 | overlook	drop	0
1392 | incorporate	disintegrate	1
1393 | live	know	0
1394 | block	recall	1
1395 | lay	back	1
1396 | restore	replace	0
1397 | promote	advertise	0
1398 | affect	regard	0
1399 | spill	mar	0
1400 | praise	censure	1
1401 | contaminate	decontaminate	1
1402 | adsorb	absorb	1
1403 | abandon	accompany	1
1404 | moisten	dry	1
1405 | end	get	1
1406 | engage	terminate	1
1407 | extend	withdraw	1
1408 | pass	hand	0
1409 | line	figure	0
1410 | retard	delay	0
1411 | criminalize	decriminalize	1
1412 | dismantle	erect	1
1413 | quarrel	agree	1
1414 | practice	employ	0
1415 | irritate	please	1
1416 | think	deem	0
1417 | cease	continue	1
1418 | cheer	urge	0
1419 | turn	translate	0
1420 | encircle	encompass	0
1421 | support	abide	0
1422 | erect	dismantle	1
1423 | imagine	think	0
1424 | undo	reverse	0
1425 | sharpen	blur	1
1426 | remember	remind	0
1427 | make	nominate	0
1428 | lie	rise	1
1429 | suck	blow	1
1430 | discover	explore	0
1431 | desire	beg	0
1432 | serve	help	0
1433 | reprise	pay	0
1434 | lose	profit	1
1435 | cushion	seat	0
1436 | violate	desecrate	0
1437 | uphold	preserve	0
1438 | see	visit	0
1439 | intrude	withdraw	1
1440 | graduate	calibrate	0
1441 | wax	become	0
1442 | embody	incorporate	0
1443 | deliver	deliberate	0
1444 | deter	dissuade	0
1445 | sin	transgress	0
1446 | undercharge	overcharge	1
1447 | let	cause	0
1448 | accumulate	scatter	1
1449 | screw	unscrew	1
1450 | prevent	permit	1
1451 | sadden	cheer	1
1452 | conduct	manage	0
1453 | sit	lie	1
1454 | intersect	cut	0
1455 | free	impede	1
1456 | supply	recall	1
1457 | joint	construct	0
1458 | hook	strike	0
1459 | glide	swim	0
1460 | matter	concern	0
1461 | assemble	convene	0
1462 | keep	allow	1
1463 | need	eliminate	1
1464 | gain	lose	1
1465 | accompany	abandon	1
1466 | screen	shield	0
1467 | elevate	demote	1
1468 | dispense	distribute	0
1469 | fall	decline	0
1470 | admit	shut	1
1471 | attract	drive	1
1472 | unwind	wind	1
1473 | decimate	eliminate	0
1474 | disapprove	approve	1
1475 | diverge	converge	1
1476 | take	decline	1
1477 | assert	vindicate	0
1478 | blame	justify	1
1479 | surge	ebb	1
1480 | revolve	rotate	0
1481 | suit	answer	0
1482 | shape	bend	0
1483 | practice	use	0
1484 | deliver	surrender	0
1485 | integrate	segregate	1
1486 | differ	concur	1
1487 | grant	refuse	1
1488 | magnify	minimise	1
1489 | ruin	protect	1
1490 | function	malfunction	1
1491 | inject	insert	0
1492 | understate	exaggerate	1
1493 | evaporate	condense	1
1494 | imitate	echo	0
1495 | destroy	consume	0
1496 | involve	require	0
1497 | bury	cover	0
1498 | legalize	decriminalize	0
1499 | blame	acquit	1
1500 | bless	curse	1
1501 | break	bust	0
1502 | discourage	encourage	1
1503 | push	pull	1
1504 | keep	permit	1
1505 | permit	prohibit	1
1506 | marry	divorce	1
1507 | charge	excite	0
1508 | starve	give	1
1509 | cross	hybridize	0
1510 | start	finish	1
1511 | specify	determine	0
1512 | count	bet	0
1513 | let	oppose	0
1514 | strike	touch	0
1515 | entice	frighten	1
1516 | lack	feature	1
1517 | ameliorate	decline	1
1518 | aggravate	worsen	0
1519 | compress	press	0
1520 | imagine	dream	0
1521 | contraindicate	indicate	1
1522 | sell	purchase	1
1523 | shrink	enlarge	1
1524 | cross	uncross	1
1525 | plead	defend	0
1526 | extinguish	kindle	1
1527 | cast	form	0
1528 | imply	exclude	1
1529 | permit	veto	1
1530 | forge	formulate	0
1531 | differ	agree	1
1532 | complain	cheer	1
1533 | conceive	suppose	0
1534 | trouble	molest	0
1535 | boost	promote	0
1536 | specify	generalize	1
1537 | prevent	aid	1
1538 | constrict	enlarge	1
1539 | succeed	replace	0
1540 | pause	cease	0
1541 | withdraw	deposit	1
1542 | shut	admit	1
1543 | recognize	spot	0
1544 | overstate	downplay	1
1545 | miss	have	1
1546 | avert	incur	1
1547 | take	disclaim	1
1548 | merge	sink	0
1549 | train	aim	0
1550 | prove	establish	0
1551 | surprise	hold	0
1552 | mind	body	1
1553 | applaud	clap	0
1554 | wake	awaken	0
1555 | eliminate	need	1
1556 | talk	rumor	0
1557 | term	condition	0
1558 | fortify	disarm	1
1559 | overwhelm	overcome	0
1560 | depend	reckon	0
1561 | doubt	believe	1
1562 | decentralize	centralize	1
1563 | unwind	roll	1
1564 | show	look	0
1565 | misrepresent	manipulate	0
1566 | accede	enter	0
1567 | disclaim	deny	0
1568 | collect	assemble	0
1569 | assign	designate	0
1570 | dilate	shorten	1
1571 | require	eliminate	1
1572 | influence	persuade	0
1573 | hunt	hawk	0
1574 | represent	prosecute	1
1575 | weaken	decline	0
1576 | bless	condemn	1
1577 | vilify	abuse	0
1578 | unwrap	wrap	1
1579 | rear	lift	0
1580 | emphasize	accent	0
1581 | tell	estimate	0
1582 | veer	back	1
1583 | break	keep	1
1584 | wager	bet	0
1585 | sedate	stimulate	1
1586 | hide	show	1
1587 | dissociate	link	1
1588 | follow	attend	0
1589 | disarm	fortify	1
1590 | calm	arouse	1
1591 | nix	allow	1
1592 | forgo	keep	1
1593 | surrender	resist	1
1594 | unfreeze	freeze	1
1595 | shoot	take	0
1596 | bend	straighten	1
1597 | symbolize	symbolise	0
1598 | wreck	restore	1
1599 | sum	comprise	0
1600 | admit	refuse	1
1601 | shape	conceive	0
1602 | compete	contend	0
1603 | title	style	0
1604 | tune	untune	1
1605 | intensify	weaken	1
1606 | abolish	establish	1
1607 | save	salvage	0
1608 | have	refuse	1
1609 | refrain	consume	1
1610 | warn	admonish	0
1611 | support	oppose	1
1612 | recommend	disapprove	1
1613 | devoice	voice	1
1614 | love	hate	1
1615 | thin	thick	1
1616 | bear	afford	0
1617 | stress	try	0
1618 | criticise	praise	1
1619 | accelerate	decelerate	1
1620 | found	plant	0
1621 | hold	defy	0
1622 | bequeath	disinherit	1
1623 | storm	attack	0
1624 | hold	relinquish	1
1625 | front	meet	0
1626 | distrust	trust	1
1627 | exaggerate	downplay	1
1628 | bully	cajole	1
1629 | buy	preempt	0
1630 | assail	defend	1
1631 | incline	turn	0
1632 | set	adjust	0
1633 | mottle	streak	0
1634 | respect	reference	0
1635 | let	forbid	1
1636 | condemn	blame	0
1637 | reform	correct	0
1638 | narrow	restrict	0
1639 | maintain	hold	0
1640 | back	face	1
1641 | persuade	deter	1
1642 | establish	demonstrate	0
1643 | detain	arrest	0
1644 | forbid	let	1
1645 | abbreviate	expand	1
1646 | know	understand	0
1647 | train	express	0
1648 | pronate	supinate	1
1649 | infer	show	0
1650 | drop	lower	0
1651 | exonerate	acquit	0
1652 | put	place	0
1653 | downplay	overstate	1
1654 | draw	push	1
1655 | moan	groan	0
1656 | enlarge	reduce	1
1657 | prevent	allow	1
1658 | absorb	emit	1
1659 | smoke	detect	0
1660 | feed	graze	0
1661 | upset	tip	0
1662 | pin	hold	0
1663 | confirm	question	1
1664 | suspect	swear	1
1665 | displace	engage	1
1666 | grab	clutch	0
1667 | accept	reject	1
1668 | predate	follow	1
1669 | enable	incapacitate	1
1670 | discover	divulge	0
1671 | destroy	extinguish	0
1672 | blur	confuse	0
1673 | weaken	strengthen	1
1674 | extend	diffuse	0
1675 | sort	fit	0
1676 | construct	make	0
1677 | cut	enlarge	1
1678 | disappoint	satisfy	1
1679 | colour	influence	0
1680 | stifle	suffocate	0
1681 | evidence	show	0
1682 | abolish	launch	1
1683 | relax	stress	1
1684 | break	upgrade	1
1685 | depress	demoralize	0
1686 | import	interest	0
1687 | change	rest	1
1688 | bring	produce	0
1689 | trust	mistrust	1
1690 | encode	decode	1
1691 | revive	renew	1
1692 | indulge	gratify	0
1693 | extinguish	ignite	1
1694 | consume	swallow	0
1695 | flee	stay	1
1696 | block	remember	1
1697 | deprive	rob	0
1698 | prefix	suffix	1
1699 | deem	consider	0
1700 | live	blank	1
1701 | will	leave	0
1702 | add	join	0
1703 | voice	devoice	1
1704 | die	vanish	0
1705 | design	invent	0
1706 | determine	fix	0
1707 | dislike	enjoy	1
1708 | tell	narrate	0
1709 | inspire	animate	0
1710 | bury	remember	1
1711 | set	sit	0
1712 | circumscribe	limit	0
1713 | puff	blow	0
1714 | wrap	unwrap	1
1715 | quicken	slow	1
1716 | come	descend	0
1717 | progress	retreat	1
1718 | germinate	die	1
1719 | fly	pilot	0
1720 | leach	percolate	0
1721 | engage	sack	1
1722 | school	tutor	0
1723 | separate	unite	1
1724 | near	close	0
1725 | betray	fail	0
1726 | face	back	1
1727 | invalidate	confirm	1
1728 | work	malfunction	1
1729 | settle	regulate	0
1730 | attribute	ascribe	0
1731 | correlate	correspond	0
1732 | invest	dress	0
1733 | discharge	charge	1
1734 | compress	decompress	1
1735 | elaborate	cut	1
1736 | affect	influence	0
1737 | clear	obscure	1
1738 | withdraw	engage	1
1739 | tie	disconnect	1
1740 | originate	rise	0
1741 | rest	recline	0
1742 | expand	abbreviate	1
1743 | minimize	maximise	1
1744 | discover	impart	0
1745 | have	lack	1
1746 | predate	postdate	1
1747 | enthrone	depose	1
1748 | disallow	let	1
1749 | draft	discharge	1
1750 | break	relegate	0
1751 | minimize	magnify	1
1752 | skew	adjust	1
1753 | absorb	incorporate	0
1754 | glorify	exalt	0
1755 | untie	tie	1
1756 | arise	descend	1
1757 | prevent	incite	1
1758 | get	contract	0
1759 | counsel	consult	0
1760 | stabilize	destabilize	1
1761 | cause	make	0
1762 | hang	exhibit	0
1763 | urge	instigate	0
1764 | protect	cushion	0
1765 | remove	add	1
1766 | contradict	substantiate	1
1767 | free	enforce	1
1768 | cool	warm	1
1769 | refuse	say	0
1770 | overvalue	undervalue	1
1771 | plow	cover	0
1772 | start	terminate	1
1773 | terminate	commence	1
1774 | breach	observe	1
1775 | praise	blame	1
1776 | equal	coordinate	0
1777 | mark	note	0
1778 | construe	interpret	0
1779 | realize	clear	0
1780 | knock	praise	1
1781 | assert	maintain	0
1782 | mean	humble	0
1783 | remember	forget	1
1784 | curse	bless	1
1785 | invent	concoct	0
1786 | disinherit	will	1
1787 | overcharge	undercharge	1
1788 | postpone	advance	1
1789 | harden	soften	1
1790 | intersect	parallel	1
1791 | deposit	fix	0
1792 | regress	proceed	1
1793 | react	return	0
1794 | malfunction	operate	1
1795 | fire	hire	1
1796 | designate	point	0
1797 | condition	train	0
1798 | catch	release	1
1799 | pot	drain	0
1800 | polish	smooth	0
1801 | generalize	specialize	1
1802 | end	commence	1
1803 | send	inflict	0
1804 | impart	grant	0
1805 | outstrip	exceed	0
1806 | decontaminate	contaminate	1
1807 | lessen	subside	0
1808 | absolve	blame	1
1809 | contradict	affirm	1
1810 | protect	expose	1
1811 | champion	advocate	0
1812 | improve	amend	0
1813 | quit	preserve	1
1814 | release	block	1
1815 | unfold	fold	1
1816 | induce	get	0
1817 | bump	raise	1
1818 | deflagrate	detonate	1
1819 | preserve	stop	1
1820 | garb	dress	0
1821 | win	fail	1
1822 | unbind	bind	1
1823 | unroll	roll	1
1824 | arrive	leave	1
1825 | implement	relieve	1
1826 | bring	institute	0
1827 | use	custom	0
1828 | accommodate	adjust	0
1829 | contract	stretch	1
1830 | straighten	flex	1
1831 | borrow	carry	1
1832 | lead	follow	1
1833 | calm	tranquilize	0
1834 | start	begin	0
1835 | please	offend	1
1836 | free	freeze	1
1837 | curve	recurve	0
1838 | match	rival	0
1839 | mention	remark	0
1840 | drag	brake	0
1841 | attend	miss	1
1842 | cut	ignore	0
1843 | blow	assault	0
1844 | undervalue	appreciate	1
1845 | overexpose	underexpose	1
1846 | obtain	receive	0
1847 | understate	overstate	1
1848 | dry	drench	1
1849 | leave	get	1
1850 | dissociate	separate	0
1851 | complain	lament	0
1852 | contract	dilate	1
1853 | fuck	have	0
1854 | conquer	triumph	0
1855 | stand	relent	1
1856 | recede	gain	1
1857 | allow	prevent	1
1858 | slay	hit	0
1859 | complicate	simplify	1
1860 | charge	discharge	1
1861 | exclude	bar	0
1862 | counterbalance	oppose	0
1863 | meditate	intend	0
1864 | complain	mutter	0
1865 | frighten	encourage	1
1866 | decline	consent	1
1867 | take	consume	0
1868 | top	base	1
1869 | deduct	add	1
1870 | honour	observe	0
1871 | acquire	evolve	0
1872 | dive	explore	0
1873 | restore	break	1
1874 | obviate	take	1
1875 | drag	draw	0
1876 | authorise	empower	0
1877 | please	displease	1
1878 | dehisce	open	0
1879 | breed	produce	0
1880 | cheer	complain	1
1881 | admit	deny	1
1882 | terminate	start	1
1883 | run	malfunction	1
1884 | embark	debark	1
1885 | meet	diverge	1
1886 | rectify	correct	0
1887 | place	grade	0
1888 | submit	accede	0
1889 | frown	smile	1
1890 | tell	differentiate	0
1891 | ring	circle	0
1892 | convict	discharge	1
1893 | depressurize	pressurize	1
1894 | rock	shake	0
1895 | maim	disable	0
1896 | excite	relax	1
1897 | rejoin	return	0
1898 | unroll	wrap	1
1899 | rush	tumble	0
1900 | interpolate	alter	0
1901 | tense	relax	1
1902 | shorten	lengthen	1
1903 | stop	check	0
1904 | cover	expose	1
1905 | fume	fret	0
1906 | accelerate	slow	1
1907 | postulate	eliminate	1
1908 | shape	regulate	0
1909 | purge	rehabilitate	1
1910 | preserve	cease	1
1911 | loop	bend	0
1912 | doff	don	1
1913 | miss	drop	0
1914 | require	obviate	1
1915 | bind	untie	1
1916 | list	border	0
1917 | recall	retrieve	0
1918 | presuppose	assume	0
1919 | terminate	employ	1
1920 | oppose	check	0
1921 | round	labialize	0
1922 | enhance	advance	0
1923 | depict	give	0
1924 | diminish	dwindle	0
1925 | inform	notify	0
1926 | imply	comprise	0
1927 | give	gift	0
1928 | drill	discipline	0
1929 | transport	shift	0
1930 | laud	celebrate	0
1931 | lower	bring	0
1932 | piece	join	0
1933 | hoe	weed	0
1934 | disrespect	respect	1
1935 | forfeit	claim	1
1936 | imitate	invent	1
1937 | disenfranchise	enfranchise	1
1938 | discharge	drop	0
1939 | consume	exhaust	0
1940 | tack	wear	1
1941 | conserve	waste	1
1942 | disengage	withdraw	0
1943 | flex	straighten	1
1944 | show	render	0
1945 | check	tick	0
1946 | free	stick	1
1947 | borrow	receive	0
1948 | begin	stop	1
1949 | simplify	complicate	1
1950 | express	squeeze	0
1951 | decline	bend	0
1952 | hire	engage	0
1953 | realise	earn	0
1954 | stay	restrain	0
1955 | discharge	draft	1
1956 | miss	strike	1
1957 | reassure	worry	1
1958 | edit	retouch	0
1959 | match	equal	0
1960 | appeal	repel	1
1961 | install	uninstall	1
1962 | lengthen	shorten	1
1963 | back	look	1
1964 | dodge	evade	0
1965 | saw	figure	0
1966 | please	delight	0
1967 | ascend	set	1
1968 | lose	advance	1
1969 | make	occasion	0
1970 | fold	open	1
1971 | decelerate	accelerate	1
1972 | dissent	accept	1
1973 | minimise	maximize	1
1974 | sport	feature	0
1975 | sell	buy	1
1976 | let	disallow	1
1977 | disconnect	tie	1
1978 | lower	raise	1
1979 | cool	heat	1
1980 | observe	offend	1
1981 | mean	base	0
1982 | dominate	predominate	0
1983 | let	veto	1
1984 | decline	have	1
1985 | dispatch	accomplish	0
1986 | bomb	fail	0
1987 | indicate	name	0
1988 | retire	progress	1
1989 | disclaim	take	1
1990 | proceed	discontinue	1
1991 | document	commission	0
1992 | acquire	lose	1
1993 | occupy	engage	0
1994 | shape	imagine	0
1995 | avoid	face	1
1996 | jeopardise	threaten	0
1997 | break	raise	1
1998 | hit	strike	0
1999 | shape	make	0
2000 | proceed	keep	0
2001 | abhor	like	1
2002 | hurl	cast	0
2003 | overstate	understate	1
2004 | sink	swim	1
2005 | soak	drain	0
2006 | land	bring	0
2007 | browse	feed	0
2008 | preserve	quit	1
2009 | classify	mix	1
2010 | battle	contend	0
2011 | touch	disturb	0
2012 | uphold	cease	1
2013 | blame	absolve	1
2014 | cut	elaborate	1
2015 | reduce	enlarge	1
2016 | settle	finalise	0
2017 | enlist	discharge	1
2018 | unify	separate	1
2019 | extend	shorten	1
2020 | disengage	lock	1
2021 | understand	interpret	0
2022 | complement	compliment	0
2023 | ask	exhibit	0
2024 | support	underpin	0
2025 | sort	adapt	0
2026 | diffuse	concentrate	1
2027 | broaden	narrow	1
2028 | saw	consider	0
2029 | leave	disown	1
2030 | reject	disapprove	0
2031 | grace	honor	0
2032 | omit	remember	1
2033 | shear	clip	0
2034 | dehydrate	hydrate	1
2035 | lie	stand	1
2036 | undermine	sabotage	0
2037 | last	dissipate	1
2038 | conceive	originate	0
2039 | protect	harass	1
2040 | anger	please	1
2041 | appear	disappear	1
2042 | hibernate	aestivate	1
2043 | urge	recommend	0
2044 | perpetrate	commit	0
2045 | urge	restrain	1
2046 | vanish	fade	0
2047 | decide	settle	0
2048 | front	rear	1
2049 | propel	push	0
2050 | mess	eat	0
2051 | have	miss	1
2052 | smash	demolish	0
2053 | solve	explain	0
2054 | break	advance	1
2055 | pimp	pander	0
2056 | borrow	derive	0
2057 | heat	chill	1
2058 | stick	dislodge	1
2059 | explain	unfold	0
2060 | discover	identify	0
2061 | magnify	reduce	1
2062 | idle	run	1
2063 | drive	attract	1
2064 | recover	retrieve	0
2065 | top	bottom	1
2066 | injure	help	1
2067 | rely	suspect	1
2068 | fetch	convey	0
2069 | end	begin	1
2070 | expose	cover	1
2071 | invalidate	validate	1
2072 | deter	persuade	1
2073 | blaze	flame	0
2074 | stay	rest	0
2075 | sound	whistle	0
2076 | smile	cry	1
2077 | work	idle	1
2078 | learn	forget	1
2079 | rebound	bounce	0
2080 | dislodge	stick	1
2081 | miss	collide	1
2082 | quit	conduct	0
2083 | defect	fail	0
2084 | captain	lead	0
2085 | intensify	fade	1
2086 | stay	quit	1
2087 | exile	repatriate	1
2088 | sack	engage	1
2089 | follow	lead	1
2090 | improve	worsen	1
2091 | abstain	indulge	1
2092 | observe	break	1
2093 | disturb	molest	0
2094 | exaggerate	understate	1
2095 | mobilize	rally	0
2096 | sack	clear	0
2097 | justify	blame	1
2098 | don	doff	1
2099 | disagree	check	1
2100 | parade	show	0
2101 | begin	finish	1
2102 | predominate	dominate	0
2103 | dilate	contract	1
2104 | quit	enter	1
2105 | exempt	apply	1
2106 | pull	repel	1
2107 | undervalue	overvalue	1
2108 | suffix	prefix	1
2109 | enquire	ask	0
2110 | incorporate	assimilate	0
2111 | depose	restore	1
2112 | read	pass	1
2113 | obey	refuse	1
2114 | suffer	support	0
2115 | injure	preserve	1
2116 | level	raise	1
2117 | float	sink	1
2118 | absorb	draw	0
2119 | darken	brighten	1
2120 | hunt	forage	0
2121 | hug	caress	0
2122 | unbolt	bolt	1
2123 | circulate	run	0
2124 | delight	enjoy	0
2125 | renovate	repair	0
2126 | labor	drive	0
2127 | recommend	oppose	1
2128 | repel	pull	1
2129 | notice	observe	0
2130 | endure	weather	0
2131 | race	speed	0
2132 | split	unify	1
2133 | delay	hasten	1
2134 | free	blame	1
2135 | accord	consent	0
2136 | bait	lure	0
2137 | fill	execute	0
2138 | straighten	curve	1
2139 | analyze	synthesize	1
2140 | raise	demote	1
2141 | syndicate	combine	0
2142 | profit	loss	1
2143 | follow	embrace	0
2144 | mind	obey	0
2145 | exaggerate	minimise	1
2146 | fear	dread	0
2147 | confine	border	0
2148 | astonish	amaze	0
2149 | exit	enter	1
2150 | agitate	calm	1
2151 | propel	rest	1
2152 | integrate	differentiate	1
2153 | defeat	frustrate	0
2154 | comfort	strengthen	0
2155 | affirm	deny	1
2156 | expend	use	0
2157 | air	style	0
2158 | ridicule	praise	1
2159 | question	wonder	0
2160 | narrow	broaden	1
2161 | cease	refrain	0
2162 | premier	premiere	0
2163 | regroup	reorganise	0
2164 | brighten	darken	1
2165 | reduce	dilate	1
2166 | interrupt	continue	1
2167 | house	dwell	0
2168 | desolate	ravage	0
2169 | meet	assemble	0
2170 | overplay	underplay	1
2171 | refuse	accept	1
2172 | think	meditate	0
2173 | bear	stand	0
2174 | begin	recommence	0
2175 | sew	tailor	0
2176 | classify	declassify	1
2177 | specialize	broaden	1
2178 | eat	see	0
2179 | depreciate	appreciate	1
2180 | veto	allow	1
2181 | follow	precede	1
2182 | mourn	wail	0
2183 | place	pose	0
2184 | equal	differ	1
2185 | prosecute	defend	1
2186 | calm	agitate	1
2187 | curtail	deprive	0
2188 | alarm	frighten	0
2189 | empathize	understand	0
2190 | aim	place	0
2191 | band	ring	0
2192 | present	introduce	0
2193 | defend	attack	1
2194 | improve	spoil	1
2195 | release	confine	1
2196 | disregard	emphasize	1
2197 | heave	wave	0
2198 | matter	form	1
2199 | transport	enchant	0
2200 | take	refuse	1
2201 | bump	advance	1
2202 | die	croak	0
2203 | avoid	validate	1
2204 | rush	linger	1
2205 | constitute	compose	0
2206 | reckon	settle	0
2207 | skate	glide	0
2208 | advance	hasten	0
2209 | shoot	dash	0
2210 | make	piss	0
2211 | contend	cope	0
2212 | gain	loss	1
2213 | disagree	agree	1
2214 | consider	revolve	0
2215 | add	contribute	0
2216 | abide	bear	0
2217 | exhort	advise	0
2218 | spy	scout	0
2219 | intend	destine	0
2220 | build	destroy	1
2221 | rate	place	0
2222 | emit	eject	0
2223 | see	look	0
2224 | reduce	quash	0
2225 | cast	mold	0
2226 | stay	hinder	0
2227 | attract	repulse	1
2228 | oppose	support	1
2229 | free	block	1
2230 | rear	front	1
2231 | recuperate	deteriorate	1
2232 | untie	bind	1
2233 | interest	excite	0
2234 | popularize	democratize	0
2235 | commence	originate	0
2236 | remain	change	1
2237 | lumber	move	0
2238 | regress	progress	1
2239 | drape	hang	0
2240 | breach	surge	0
2241 | accord	harmonize	0
2242 | hasten	retard	1
2243 | drop	recover	1
2244 | use	employ	0
2245 | deport	banish	0
2246 | hunt	grouse	0
2247 | put	divest	1
2248 | accent	emphasize	0
2249 | discontinue	uphold	1
2250 | postpone	delay	0
2251 | imprison	deliver	1
2252 | adhere	hold	0
2253 | expand	shorten	1
2254 | begin	cease	1
2255 | rush	detain	1
2256 | demote	upgrade	1
2257 | break	promote	1
2258 | quit	continue	1
2259 | garner	distribute	1
2260 | lack	have	1
2261 | scandalise	shock	0
2262 | light	fall	0
2263 | boycott	avoid	0
2264 | recall	block	1
2265 | cancel	limit	0
2266 | extinguish	create	1
2267 | back	front	1
2268 | stop	preserve	1
2269 | dematerialize	materialize	1
2270 | decline	incline	1
2271 | count	rely	0
2272 | judge	gauge	0
2273 | purge	purify	0
2274 | decide	adjudicate	0
2275 | repel	draw	1
2276 | yield	resign	0
2277 | demote	elevate	1
2278 | bomb	pass	1
2279 | debark	embark	1
2280 | enlarge	shorten	1
2281 | leave	put	0
2282 | win	lose	1
2283 | prefer	choose	0
2284 | improve	deteriorate	1
2285 | magnify	downplay	1
2286 | prohibit	forbid	0
2287 | encounter	conflict	0
2288 | reply	rejoin	0
2289 | upset	disrupt	0
2290 | concur	approve	0
2291 | skew	align	1
2292 | practise	practice	0
2293 | employ	sack	1
2294 | block	release	1
2295 | fire	engage	1
2296 | imprison	free	1
2297 | escape	evade	0
2298 | mature	complete	0
2299 | eliminate	take	1
2300 | reconstruct	reform	0
2301 | know	guess	1
2302 | indicate	signal	0
2303 | miss	want	0
2304 | borrow	return	1
2305 | dismantle	assemble	1
2306 | conceal	admit	1
2307 | originate	imitate	1
2308 | move	rest	1
2309 | confiscate	seize	0
2310 | oblige	please	0
2311 | purge	remove	0
2312 | forget	reminisce	1
2313 | proceed	arise	0
2314 | induce	deduce	1
2315 | delay	filibuster	0
2316 | allow	deny	1
2317 | communicate	impart	0
2318 | expand	cut	1
2319 | keep	let	1
2320 | exclaim	proclaim	0
2321 | put	push	0
2322 | propel	send	0
2323 | retard	slow	0
2324 | grant	allot	0
2325 | assess	evaluate	0
2326 | sustain	defend	0
2327 | nip	bite	0
2328 | turn	fashion	0
2329 | exceed	outperform	0
2330 | buy	grant	1
2331 | scatter	spill	0
2332 | enlarge	contract	1
2333 | transgress	observe	1
2334 | shift	trick	0
2335 | aggravate	exacerbate	0
2336 | inflame	ignite	0
2337 | ebb	flow	1
2338 | lactate	suckle	0
2339 | reject	have	1
2340 | die	fail	0
2341 | empty	fill	1
2342 | approve	disapprove	1
2343 | commence	terminate	1
2344 | collect	spread	1
2345 | block	disengage	1
2346 | attract	repel	1
2347 | demote	advance	1
2348 | frame	produce	0
2349 | bake	broil	0
2350 | maximise	minimize	1
2351 | liberate	detain	1
2352 | decline	better	1
2353 | object	end	0
2354 | make	gain	0
2355 | listen	obey	0
2356 | consume	use	0
2357 | invest	disinvest	1
2358 | charter	hire	0
2359 | find	bump	0
2360 | disengage	block	1
2361 | magnify	minimize	1
2362 | reckon	depend	0
2363 | eliminate	decimate	0
2364 | veto	let	1
2365 | criticize	praise	1
2366 | default	pay	1
2367 | thick	thin	1
2368 | complete	realize	0
2369 | beat	trouble	0
2370 | amplify	minimize	1
2371 | mock	disappoint	0
2372 | free	lodge	1
2373 | assemble	dismantle	1
2374 | overturn	subvert	0
2375 | beg	reject	1
2376 | maintain	conserve	0
2377 | forecast	project	0
2378 | free	wedge	1
2379 | catch	enchant	0
2380 | drop	recuperate	1
2381 | turn	shape	0
2382 | give	cause	0
2383 | miss	hit	1
2384 | plant	fix	0
2385 | demean	degrade	0
2386 | solicit	try	0
2387 | take	abstain	1
2388 | rest	rely	0
2389 | revoke	enact	1
2390 | liberate	confine	1
2391 | get	leave	1
2392 | omit	slip	0
2393 | demonstrate	disprove	1
2394 | collapse	founder	0
2395 | unfold	display	0
2396 | legalise	outlaw	1
2397 | clean	dirty	1
2398 | remain	persist	0
2399 | tear	rip	0
2400 | oppress	violate	0
2401 | stop	continue	1
2402 | extrapolate	interpolate	1
2403 | associate	disassociate	1
2404 | settle	compose	0
2405 | deteriorate	recover	1
2406 | issue	terminate	0
2407 | implement	apply	0
2408 | evince	express	0
2409 | echo	ring	0
2410 | imagine	figure	0
2411 | conform	deviate	1
2412 | object	agree	1
2413 | implant	insert	0
2414 | image	project	0
2415 | blur	focus	1
2416 | issue	emerge	0
2417 | decrypt	encode	1
2418 | flow	ebb	1
2419 | dictate	order	0
2420 | design	designate	0
2421 | procure	solicit	0
2422 | contract	enlarge	1
2423 | gasp	labor	0
2424 | ridicule	satirize	0
2425 | disprove	establish	1
2426 | defy	obey	1
2427 | clear	brighten	0
2428 | stop	start	1
2429 | prevent	prohibit	0
2430 | desegregate	integrate	0
2431 | lay	consist	0
2432 | train	educate	0
2433 | arrive	depart	1
2434 | insure	secure	0
2435 | support	hold	0
2436 | compile	amass	0
2437 | stretch	shrink	1
2438 | expel	exclude	0
2439 | wound	cut	0
2440 | disregard	mention	1
2441 | lactate	nurse	0
2442 | increase	decrease	1
2443 | bind	obligate	0
2444 | retire	arise	1
2445 | block	unblock	1
2446 | wall	fortify	0
2447 | coil	uncoil	1
2448 | downplay	amplify	1
2449 | know	ignore	1
2450 | forage	feed	0
2451 | jerk	press	1
2452 | restrain	suppress	0
2453 | start	halt	1
2454 | educate	enlighten	0
2455 | spend	waste	0
2456 | stop	discontinue	0
2457 | shorten	enlarge	1
2458 | press	pressure	0
2459 | wind	unwind	1
2460 | exude	absorb	1
2461 | outstrip	pass	0
2462 | specialize	generalize	1
2463 | process	serve	0
2464 | coagulate	dissolve	1
2465 | home	close	0
2466 | dismiss	drop	0
2467 | catch	snatch	0
2468 | ignite	extinguish	1
2469 | relax	excite	1
2470 | prohibit	allow	1
2471 | exalt	glorify	0
2472 | drink	revel	0
2473 | bulge	start	0
2474 | usher	announce	0
2475 | alter	falsify	0
2476 | finish	start	1
2477 | consign	agree	0
2478 | sponsor	boycott	1
2479 | commence	end	1
2480 | establish	institute	0
2481 | fail	win	1
2482 | lift	descend	1
2483 | disagree	hold	1
2484 | command	control	0
2485 | knap	chip	0
2486 | demagnetize	magnetize	1
2487 | make	undo	1
2488 | fortify	arm	0
2489 | abstain	consume	1
2490 | supplant	remove	0
2491 | downplay	highlight	1
2492 | tame	domesticate	0
2493 | effect	operate	0
2494 | synthesise	analyse	1
2495 | lower	lift	1
2496 | overcome	rush	0
2497 | account	value	0
2498 | work	stagnate	1
2499 | issue	recall	1
2500 | track	pitch	0
2501 | pass	overtake	0
2502 | muff	catch	1
2503 | trace	track	0
2504 | relate	detail	0
2505 | germinate	cause	0
2506 | redeem	abandon	1
2507 | overturn	destroy	0
2508 | bear	gestate	0
2509 | lift	fall	1
2510 | nullify	void	0
2511 | cost	cause	0
2512 | put	offer	0
2513 | braid	lace	0
2514 | groom	prepare	0
2515 | hold	grip	0
2516 | depict	express	0
2517 | try	stress	0
2518 | repair	restore	0
2519 | lift	lower	1
2520 | supply	render	0
2521 | extemporize	improvise	0
2522 | scatter	congregate	1
2523 | support	corroborate	0
2524 | downstream	upstream	1
2525 | intimidate	bully	0
2526 | follow	predate	1
2527 | curve	straighten	1
2528 | oust	accept	1
2529 | defend	forbid	0
2530 | put	fix	0
2531 | exceed	fail	1
2532 | unpin	pin	1
2533 | shock	outrage	0
2534 | direct	organize	0
2535 | 


--------------------------------------------------------------------------------
/dataset/verb-pairs.val:
--------------------------------------------------------------------------------
  1 | lean	list	0
  2 | move	stay	1
  3 | disappear	appear	1
  4 | increase	diminish	1
  5 | allow	keep	1
  6 | stand	rank	0
  7 | rise	come	0
  8 | decriminalize	criminalize	1
  9 | stay	depart	1
 10 | leave	relinquish	0
 11 | disprove	show	1
 12 | strike	miss	1
 13 | applaud	condemn	1
 14 | endeavor	try	0
 15 | mature	perfect	0
 16 | hydrate	dehydrate	1
 17 | shrink	grow	1
 18 | abduct	adduct	1
 19 | persuade	dissuade	1
 20 | lay	suppress	0
 21 | absorb	assimilate	0
 22 | echo	resound	0
 23 | turn	ferment	0
 24 | chop	divide	0
 25 | motivate	incite	0
 26 | fence	argue	0
 27 | cure	heal	0
 28 | deprive	enrich	1
 29 | drift	wander	0
 30 | mediate	intercede	0
 31 | ignore	consider	1
 32 | retreat	shelter	0
 33 | dispute	confirm	1
 34 | catch	hitch	0
 35 | acquit	carry	0
 36 | comment	commentate	0
 37 | stretch	contract	1
 38 | destroy	overthrow	0
 39 | ameliorate	exacerbate	1
 40 | see	discern	0
 41 | slow	accelerate	1
 42 | allow	proscribe	1
 43 | listen	eavesdrop	0
 44 | veil	unveil	1
 45 | receive	take	0
 46 | catch	refrain	0
 47 | sharpen	soften	1
 48 | respect	honour	0
 49 | protect	plunder	1
 50 | thwart	frustrate	0
 51 | flee	depart	0
 52 | stand	soften	1
 53 | recommend	discourage	1
 54 | trace	imitate	0
 55 | enter	exit	1
 56 | verify	assert	0
 57 | fizzle	fail	0
 58 | herald	hail	0
 59 | live	exist	0
 60 | scatter	dot	0
 61 | maximize	minimize	1
 62 | tie	constrain	0
 63 | agitate	disturb	0
 64 | forget	retrieve	1
 65 | detain	liberate	1
 66 | lack	fault	0
 67 | leave	desist	0
 68 | form	constitute	0
 69 | become	get	0
 70 | enthrone	dethrone	1
 71 | employ	displace	1
 72 | side	match	0
 73 | lose	regain	1
 74 | ascend	descend	1
 75 | keep	discontinue	1
 76 | change	mutate	0
 77 | allow	forbid	1
 78 | stump	speak	0
 79 | field	bat	1
 80 | diminish	increase	1
 81 | slow	speed	1
 82 | imagine	envisage	0
 83 | haul	veer	1
 84 | scramble	struggle	0
 85 | operate	act	0
 86 | attack	invade	0
 87 | disregard	observe	1
 88 | recognize	realize	0
 89 | acquit	clear	0
 90 | apply	resist	1
 91 | encode	decipher	1
 92 | distribute	collect	1
 93 | benefit	help	0
 94 | disconnect	connect	1
 95 | appeal	summon	0
 96 | scatter	gather	1
 97 | impregnate	fertilize	0
 98 | catch	draft	0
 99 | alter	continue	1
100 | loan	borrow	1
101 | work	make	0
102 | reclaim	reform	0
103 | fill	discharge	0
104 | enter	leave	1
105 | extinguish	light	1
106 | believe	discredit	1
107 | demand	eliminate	1
108 | promulgate	publish	0
109 | obviate	need	1
110 | hold	disagree	1
111 | lend	borrow	1
112 | encrypt	decrypt	1
113 | free	apply	1
114 | divest	put	1
115 | dead	alive	1
116 | catch	watch	0
117 | recollect	forget	1
118 | smile	frown	1
119 | conform	diverge	1
120 | sink	bury	0
121 | lament	complain	0
122 | realize	recognise	0
123 | cause	breed	0
124 | behave	misbehave	1
125 | manifest	demonstrate	0
126 | port	starboard	1
127 | order	ordain	0
128 | buck	note	0
129 | pass	flunk	1
130 | mind	attend	0
131 | wind	twist	0
132 | exhaust	beat	0
133 | inform	teach	0
134 | immortalize	record	0
135 | agree	disagree	1
136 | follow	adopt	0
137 | intimidate	overawe	0
138 | prosecute	represent	1
139 | walk	nick	0
140 | disclose	tell	0
141 | maintain	alter	1
142 | designate	intend	0
143 | stock	store	0
144 | repulse	pull	1
145 | spread	strew	0
146 | present	future	1
147 | fall	rise	1
148 | flip	snap	0
149 | turn	tack	0
150 | reject	take	1
151 | order	commission	0
152 | forgo	claim	1
153 | wrap	unroll	1
154 | recall	supply	1
155 | participate	quit	1
156 | present	gift	0
157 | terminate	get	1
158 | outrage	offend	0
159 | note	ignore	1
160 | exhale	inhale	1
161 | pursue	imitate	0
162 | saw	find	0
163 | scold	praise	1
164 | darken	lighten	1
165 | evade	dodge	0
166 | enforce	free	1
167 | forbid	permit	1
168 | trade	switch	0
169 | reserve	book	0
170 | cease	begin	1
171 | consume	abstain	1
172 | discredit	believe	1
173 | honor	dishonor	1
174 | counteract	neutralize	0
175 | seal	unseal	1
176 | soothe	compose	0
177 | praise	scold	1
178 | kick	cheer	1
179 | fix	rest	0
180 | hug	embrace	0
181 | follow	forego	1
182 | rejoice	cry	1
183 | 


--------------------------------------------------------------------------------
/preprocess/create_dataset.py:
--------------------------------------------------------------------------------
  1 | import random
  2 | import numpy
  3 | import math
  4 | import argparse
  5 | from common import Resources
  6 | 
  7 | NEG_POS_RATIO = 1
  8 | TRAIN_PORTION = 0.7
  9 | TEST_PORTION = 0.25
 10 | VALID_PORTION = 0.05
 11 | 
 12 | def main():
 13 |     """
 14 |     
 15 |     """
 16 |     parser = argparse.ArgumentParser()
 17 |     parser.add_argument('-corpus', type=str)
 18 |     parser.add_argument('-pos', type=str)
 19 |     parser.add_argument('-neg', type=str)
 20 |     parser.add_argument('-prefix', type=str)
 21 |     parser.add_argument('-min', type=int)
 22 |     
 23 |     args = parser.parse_args()
 24 |     corpus_prefix = args.corpus
 25 |     pos_file = args.pos
 26 |     neg_file = args.neg
 27 |     dataset_prefix = args.prefix
 28 |     min_occurrences = args.min
 29 |     
 30 |     # Load the resource (processed corpus)
 31 |     print 'Loading the corpus...'
 32 |     corpus = Resources(corpus_prefix)
 33 |     
 34 |     print 'Loading the dataset...'
 35 |     pos_pairs = load_dataset(pos_file)
 36 |     neg_pairs = load_dataset(neg_file)
 37 |     
 38 |     print 'Filtering out word-pairs...'
 39 |     filtered_pos_pairs = filter_word_pairs(corpus, pos_pairs.keys(), min_occurrences)
 40 |     filtered_neg_pairs = filter_word_pairs(corpus, neg_pairs.keys(), min_occurrences)
 41 |     
 42 |     positives, negatives = keep_ratio(filtered_pos_pairs, filtered_neg_pairs)
 43 |     
 44 |     pos_train_set, pos_test_set, pos_valid_set = split_dataset(positives, pos_pairs)
 45 |     neg_train_set, neg_test_set, neg_valid_set = split_dataset(negatives, neg_pairs)
 46 |     
 47 |     train_set_x = pos_train_set[0] + neg_train_set[0]
 48 |     train_set_y = pos_train_set[1] + neg_train_set[1]
 49 |     test_set_x = pos_test_set[0] + neg_test_set[0]
 50 |     test_set_y = pos_test_set[1] + neg_test_set[1]
 51 |     valid_set_x = pos_valid_set[0] + neg_valid_set[0]
 52 |     valid_set_y = pos_valid_set[1] + neg_valid_set[1]
 53 |         
 54 |     with open(dataset_prefix + '.train', 'wb') as f:
 55 |         for (x,y), label in zip(train_set_x, train_set_y):
 56 |             st = x + '\t' + y + '\t' + str(label) + '\n'
 57 |             f.write(st)
 58 |     with open(dataset_prefix + '.test', 'wb') as f:
 59 |         for (x,y), label in zip(test_set_x, test_set_y):
 60 |             st = x + '\t' + y + '\t' + str(label) + '\n'
 61 |             f.write(st)
 62 |     with open(dataset_prefix + '.valid', 'wb') as f:
 63 |         for (x,y), label in zip(valid_set_x, valid_set_y):
 64 |             st = x + '\t' + y + '\t' + str(label) + '\n'
 65 |             f.write(st)
 66 |             
 67 |     print 'Done........!'
 68 |     
 69 | def keep_ratio(pos_pairs, neg_pairs):
 70 |     """
 71 |     Keeps the ratio between postive and negative
 72 |     """
 73 |     if len(neg_pairs) > len(pos_pairs) * NEG_POS_RATIO:
 74 |         negatives = random.sample(neg_pairs, len(neg_pairs) * NEG_POS_RATIO)
 75 |         random.shuffle(pos_pairs)
 76 |         positives = pos_pairs
 77 |     else:
 78 |         positives = random.sample(pos_pairs, int(math.ceil(len(neg_pairs) / NEG_POS_RATIO)))
 79 |         random.shuffle(neg_pairs)
 80 |         negatives = neg_pairs
 81 |         
 82 |     return positives, negatives
 83 | 
 84 | def load_dataset(infile):
 85 |     """
 86 |     Loads dataset file
 87 |     """
 88 |     with open(infile, 'rb') as f:
 89 |         lines = [tuple(line.strip().lower().split('\t')) for line in f]
 90 |         dataset = {(x,y) : int(label) for (x,y,label) in lines}
 91 |     return dataset
 92 | 
 93 | def filter_word_pairs(corpus, dataset_keys, min_occurrences=5):
 94 |     """
 95 |     Filter out pairs from the dataset, to keep only those with enough path occurrences in the corpus
 96 |     """
 97 |     first_filter = [(x, y) for (x, y) in dataset_keys if len(x) > 2 and len(y) > 2 and
 98 |                     len(set(x.split(' ')).intersection(y.split(' '))) == 0]
 99 |     keys = [(corpus.get_id_by_term(str(x)), corpus.get_id_by_term(str(y))) for (x, y) in first_filter]
100 |     paths_x_to_y = [set(get_patterns(corpus, x_id, y_id)) for (x_id, y_id) in keys]
101 |     filtered_keys = [first_filter[i] for i, key in enumerate(keys) if len(paths_x_to_y[i]) >= min_occurrences]
102 | 
103 |     return filtered_keys
104 | 
105 | def get_patterns(corpus, x, y):
106 |     """
107 |     Returns the patterns between (x, y) term-pair
108 |     """
109 |     x_to_y_paths = corpus.get_relations(x, y)
110 |     paths = [path_id for path_id in x_to_y_paths.keys()]
111 |     return paths
112 | 
113 | def split_dataset(word_pairs, dict_word_pairs):
114 |     """
115 |     Splits dataset to train, test and valid sets
116 |     """
117 |     data_x = word_pairs
118 |     data_y = [dict_word_pairs[(x,y)] for (x,y) in data_x]
119 |     
120 |     n_samples = len(data_x)
121 |     n_train = int(numpy.round(n_samples * TRAIN_PORTION))
122 |     n_valid = int(numpy.round(n_samples * (1. - VALID_PORTION)))
123 |     
124 |     sidx = numpy.random.permutation(n_samples)
125 |     train_set_x = [data_x[s] for s in sidx[ : n_train]]
126 |     train_set_y = [data_y[s] for s in sidx[ : n_train]]
127 |     test_set_x = [data_x[s] for s in sidx[n_train : n_valid]]
128 |     test_set_y = [data_y[s] for s in sidx[n_train : n_valid]]
129 |     valid_set_x = [data_x[s] for s in sidx[n_valid : ]]
130 |     valid_set_y = [data_y[s] for s in sidx[n_valid : ]]
131 |     
132 |     train_set = (train_set_x, train_set_y)
133 |     test_set = (test_set_x, test_set_y)
134 |     valid_set = (valid_set_x, valid_set_y)
135 |     
136 |     return train_set, test_set, valid_set
137 | 
138 | if __name__=='__main__':
139 |     main()
140 |     


--------------------------------------------------------------------------------
/preprocess/create_resources.py:
--------------------------------------------------------------------------------
  1 | import gzip
  2 | import cPickle
  3 | import argparse
  4 | from collections import defaultdict
  5 | from itertools import count
  6 | 
  7 | def main():
  8 |     """
  9 |     Creates the resource from triplets file
 10 |     Usage:
 11 |         create_resource.py -input <triplets_file> -freq <frequent_paths_file> -prefix <resource_prefix>
 12 | 
 13 |         <triplets_file> = the file that contains text triplets, formated as X \tY \t path
 14 |         <frequent_paths_file> = the file containing the frequent paths. It could be created by using 
 15 |         the triplet files as follows:
 16 |         sort -u <triplets_file> | cut -f3 -d$'\t' > paths
 17 |         awk -F$'\t' '{a[$1]++; if (a[$1] == 5) print $1}' paths > frequent_paths
 18 |         <resource_prefix> = the file names' prefix for the resource files
 19 |     """
 20 |     parser = argparse.ArgumentParser()
 21 |     parser.add_argument('-input', type=str)
 22 |     parser.add_argument('-freq', type=str)
 23 |     parser.add_argument('-prefix', type=str)
 24 |     args = parser.parse_args()
 25 |     
 26 |     triplets_file = args.input
 27 |     frequent_paths_file = args.freq
 28 |     resource_prefix = args.prefix
 29 |     
 30 |     # Load the frequent paths
 31 |     with gzip.open(frequent_paths_file, 'rb') as f:
 32 |         frequent_paths = set([line.strip() for line in f])
 33 |     print 'The number of frequent paths: %d' %len(frequent_paths)
 34 |     
 35 |     paths = list(set(frequent_paths))
 36 |     left = defaultdict(count(0).next)
 37 |     right = defaultdict(count(0).next)
 38 |     # Load the corpus
 39 |     with gzip.open(triplets_file, 'rb') as f:
 40 |         for line in f:
 41 |             if len(line.strip().split('\t'))==3:
 42 |                 l, r, p = line.strip().split('\t')
 43 |                 left[l]
 44 |                 right[r]
 45 |     print 'Read triples successfully!'
 46 |           
 47 |     entities = list(set(left.keys()).union(set(right.keys())))
 48 |     term_to_id = { t : i for i, t in enumerate(entities) }
 49 |     path_to_id = { p : i for i, p in enumerate(paths) }
 50 | 
 51 |     # Terms
 52 |     term_to_id_db = {}
 53 |     id_to_term_db = {}
 54 |     
 55 |     for term, id in term_to_id.iteritems():
 56 |         id, term = str(id), str(term)
 57 |         term_to_id_db[term] = id
 58 |         id_to_term_db[id] = term
 59 |     
 60 |     cPickle.dump(term_to_id_db, open(resource_prefix + '_term_to_id.p', 'wb'))
 61 |     cPickle.dump(id_to_term_db, open(resource_prefix + '_id_to_term.p', 'wb'))       
 62 |     print 'Created term databases...'
 63 | 
 64 |     # Paths
 65 |     path_to_id_db = {}
 66 |     id_to_path_db = {}
 67 |     
 68 |     for path, id in path_to_id.iteritems():
 69 |         id, path = str(id), str(path)
 70 |         path_to_id_db[path] = id
 71 |         id_to_path_db[id] = path
 72 |         
 73 |     cPickle.dump(path_to_id_db, open(resource_prefix + '_path_to_id.p', 'wb'))
 74 |     cPickle.dump(id_to_path_db, open(resource_prefix + '_id_to_path.p', 'wb'))
 75 |     print 'Created path databases...'
 76 |     
 77 |     # Relations
 78 |     patterns_db = {}
 79 |     num_line = 0
 80 | 
 81 |     # Load the triplets file
 82 |     edges = defaultdict(lambda : defaultdict(lambda : defaultdict(int)))
 83 |     print 'Creating patterns.... '
 84 |     paths = set(paths)
 85 |     with gzip.open(triplets_file) as f:
 86 |         for line in f:
 87 |             try:
 88 |                 x, y, path = line.strip().split('\t')
 89 |             except:
 90 |                 print line
 91 |                 continue
 92 | 
 93 |             # Frequent path
 94 |             if path in paths:
 95 |                 x_id, y_id, path_id = term_to_id.get(x, -1), term_to_id.get(y, -1), path_to_id.get(path, -1)
 96 |                 if x_id > -1 and y_id > -1 and path_id > -1:
 97 |                     edges[x_id][y_id][path_id] += 1
 98 | 
 99 |             num_line += 1
100 |             if num_line % 1000000 == 0:
101 |                 print 'Processed ', num_line, ' lines.'
102 | 
103 |     for x in edges.keys():
104 |         for y in edges[x].keys():
105 |             patterns_db[str(x) + '###' + str(y)] = ','.join(
106 |                 [':'.join((str(p), str(val))) for (p, val) in edges[x][y].iteritems()])
107 |     
108 |     cPickle.dump(patterns_db, open(resource_prefix + '_patterns.p', 'wb'))
109 |     print 'Done.............!'
110 | 
111 | if __name__ == '__main__':
112 |     main()
113 | 


--------------------------------------------------------------------------------
/preprocess/parse_corpus.py:
--------------------------------------------------------------------------------
  1 | import spacy
  2 | from spacy.en import English
  3 | import networkx as nx
  4 | import argparse
  5 | import gzip
  6 | 
  7 | MAX_PATH_LEN = 11
  8 | 
  9 | def main():
 10 |     """
 11 |     Creates simple paths between target pairs in the dataset.
 12 |     :param: -input: a plain-text corpus file
 13 |     :param: -pos: part-of-speech of word class which is used to induce patterns (NN | JJ | VB)
 14 |             NN: for noun pairs
 15 |             JJ: for adjective pairs
 16 |             VN: for verb pairs
 17 |     Usage: python parse_corpus.py -input <corpus_file> -pos <part-of-speech>
 18 |     """
 19 |     parser = argparse.ArgumentParser()
 20 |     parser.add_argument('-input', type=str)
 21 |     parser.add_argument('-pos', type=str)
 22 |     args = parser.parse_args()
 23 |     
 24 |     nlp = English()
 25 |     with gzip.open(args.input, 'rb') as fin:
 26 |         with gzip.open(args.input  + '_' + args.pos + '_parsed.gz', 'wb') as fout:
 27 |             para_num = 0
 28 |             # Read each paragraph in corpus
 29 |             for paragraph in fin:
 30 |                 # Check empty paragraph
 31 |                 paragraph = paragraph.strip()
 32 |                 if len(paragraph) == 0: continue
 33 |                 para_num += 1
 34 |                 print 'Processing para: %d' %para_num
 35 |                 # Parse each sentence
 36 |                 parsed_para = nlp(unicode(paragraph))
 37 |                 for sent in parsed_para.sents:
 38 |                     simple_paths = parse_sentence(sent, args.pos)
 39 |                     if len(simple_paths) > 0:
 40 |                         print >>fout, '\n'.join(['\t'.join(path) for path in simple_paths])
 41 |     print 'Parsing done.........!'
 42 | 
 43 | def parse_sentence(sent, pos):
 44 |     """
 45 |     Returns simple paths of pairs corresponding to POS
 46 |     :sent: one sentence
 47 |     :pos: part-of-speech is used to induce patterns (NN | JJ | VB)
 48 |     """
 49 |     tokens = []
 50 |     edges = {}
 51 |     nodes = []
 52 |     pos_dict = {}
 53 |     dep_dict = {}
 54 |     # Get POS tokens
 55 |     for token in sent:
 56 |         # Adds the index of token to avoid representing many tokens by only one node
 57 |         token_with_idx = '#'.join([token_to_lemma(token), str(token.idx)])
 58 |         if token.tag_[:2] == pos and len(token.string.strip()) > 2:
 59 |             tokens.append(token_with_idx) 
 60 |             
 61 |         pos_dict[token_with_idx] = token.pos_       
 62 |         # Builds edges and nodes for graph
 63 |         node = '#'.join([token_to_lemma(token), str(token.idx)])
 64 |         head_node = '#'.join([token_to_lemma(token.head), str(token.head.idx)])
 65 |         if token.dep_ != 'ROOT': 
 66 |             edges[(head_node, node)] = token.dep_ 
 67 |             dep_dict[token_with_idx] = token.dep_  
 68 |         else:
 69 |             dep_dict[node] = 'ROOT'
 70 |             
 71 |         nodes.append(node)
 72 |         
 73 |     # Creates word pairs across word classes
 74 |     word_pairs = [(tokens[x], tokens[y]) for x in range(len(tokens)-1) 
 75 |                   for y in xrange(x+1,len(tokens))]
 76 |     # Finds dependency paths of word pairs
 77 |     simple_paths = build_simple_paths(word_pairs, edges, nodes, pos_dict, dep_dict)
 78 |     
 79 |     return simple_paths
 80 | 
 81 | def build_simple_paths(word_pairs, edges, nodes, pos_dict, dep_dict):
 82 |     """
 83 |     Finds the paths of all word pairs in a sentence. Firstly, checks (x,y) or (y,x) in list of target pairs. 
 84 |     If 'Yes', finds paths from x to y (y to x).
 85 |     :param word_pairs: contains all word pairs in a sentence
 86 |     :param edges: edges of the dependency tree in a sentence, using to build graph
 87 |     :param nodes: nodes of the dependency tree in a sentence (according to tokens), using to build graph
 88 |     :return: list of paths of all word pairs.
 89 |     """
 90 |     simple_paths = []
 91 |     for (x,y) in word_pairs:
 92 |         x_token, y_token = x.split('#')[0], y.split('#')[0]
 93 |         if x_token != y_token:
 94 |             x_to_y_paths = simple_path((x, y), edges, nodes, pos_dict, dep_dict)
 95 |             simple_paths.extend([x_token, y_token, ':::'.join(path)] for path in x_to_y_paths if len(path) > 0)
 96 |             y_to_x_paths = simple_path((y, x), edges, nodes, pos_dict, dep_dict)
 97 |             simple_paths.extend([y_token, x_token, ':::'.join(path)] for path in y_to_x_paths if len(path) > 0)
 98 | 
 99 |     return simple_paths
100 | 
101 | def simple_path((x,y), edges, nodes, pos_dict, dep_dict):
102 |     """
103 |     Returns the simple dependency paths between x and y, using the simple paths \
104 |     in the graph of dependency tree.
105 |     :param edges: the edges of the graph
106 |     :param nodes: the nodes of the graph
107 |     :return: the simple paths between x and y in which each node is normalized by lemma/pos/dep/dist
108 |     """
109 |     # Gets edges without indices from edges
110 |     edges_with_idx = [k for k in edges.keys()]
111 |     # Builds graph
112 |     G = nx.Graph()
113 |     G.add_nodes_from(nodes)
114 |     G.add_edges_from(edges_with_idx)
115 |     # Finds paths from x to y and paths from y to x
116 |     x_to_y_paths = [path for path in nx.all_simple_paths(G,source=x, target=y)]
117 |     y_to_x_paths = [path for path in nx.all_simple_paths(G,source=y, target=x)]
118 |     # Normalizes simple paths
119 |     normalized_simple_paths = []
120 |     for path in x_to_y_paths:
121 |         _paths = simple_path_normalization(path, edges, pos_dict, dep_dict)
122 |         if _paths is not None:
123 |             normalized_simple_paths.append(_paths)
124 |     for path in y_to_x_paths:
125 |         _paths = simple_path_normalization(path, edges, pos_dict, dep_dict)
126 |         if _paths is not None:
127 |             normalized_simple_paths.append(_paths)
128 |     
129 |     return normalized_simple_paths
130 | 
131 | def simple_path_normalization(path, edges, pos_dict, dep_dict):
132 |     """
133 |     Returns the simple path from x to y
134 |     """
135 |     path_len = len(path)
136 |     if path_len <= MAX_PATH_LEN:
137 |         if path_len == 2:
138 |             x_token, y_token = path[0], path[1]
139 |             if edges.has_key((path[0],path[1])):
140 |                 x_to_y_path = ['X/' + pos_dict[x_token] + '/' + dep_dict[x_token] + '/' + str(0), 
141 |                                'Y/' + pos_dict[y_token] + '/' + dep_dict[y_token] + '/' + str(1)]
142 |             else:
143 |                 x_to_y_path = ['X/' + pos_dict[x_token] + '/' + dep_dict[x_token] + '/' + str(1), 
144 |                                'Y/' + pos_dict[y_token] + '/' + dep_dict[y_token] + '/' + str(0)]
145 |         else:
146 |             dist = relative_distance(path, edges)
147 |             x_to_y_path = []
148 |             for idx in range(path_len):
149 |                 idx_token = path[idx]
150 |                 if idx == 0:
151 |                     source_node = 'X/' + pos_dict[idx_token] + '/' + dep_dict[idx_token] + '/' + str(dist[idx])
152 |                     x_to_y_path.extend([source_node])
153 |                 elif idx == path_len - 1:
154 |                     target_node = 'Y/' + pos_dict[idx_token] + '/' + dep_dict[idx_token] + '/' + str(dist[idx])
155 |                     x_to_y_path.extend([target_node])
156 |                 else:
157 |                     lemma = idx_token.split('#')[0]
158 |                     node = lemma + '/' + pos_dict[idx_token] + '/' + \
159 |                             dep_dict[idx_token] + '/' + str(dist[idx])
160 |                     x_to_y_path.extend([node])           
161 |         return x_to_y_path if len(x_to_y_path) > 0 else None
162 |     else:
163 |         return None
164 | 
165 | def relative_distance(path, edges):
166 |     """
167 |     Returns the relative distance between the ancestor node and others
168 |     """
169 |     root_idx = -1
170 |     dist = []
171 |     for idx in range(len(path)-1):
172 |         current_node = path[idx]        
173 |         next_node = path[idx+1]
174 |         if edges.has_key((current_node,next_node)):
175 |             root_idx = idx
176 |             break
177 |     if root_idx == -1:
178 |         for i in range(len(path)):
179 |             dist.append(len(path) - i - 1)
180 |     else:
181 |         for i in range(len(path)):
182 |             dist.append(abs(root_idx-i))
183 |     return dist
184 | 
185 | def token_to_string(token):
186 |     """
187 |     Converts the token to string representation
188 |     :param token:
189 |     :return: lower string representation of the token
190 |     """
191 |     if not isinstance(token, spacy.tokens.token.Token):
192 |         return ' '.join([t.string.strip().lower() for t in token])
193 |     else:
194 |         return token.string.strip().lower()
195 | 
196 | def token_to_lemma(token):
197 |     """
198 |     Converts the token to string representation
199 |     :param token: the token
200 |     :return: string representation of the token
201 |     """
202 |     if not isinstance(token, spacy.tokens.token.Token):
203 |         return token_to_string(token)
204 |     else:
205 |         return token.lemma_.strip().lower()
206 | 
207 | if __name__=='__main__':
208 |     main()   
209 |                     
210 | 


--------------------------------------------------------------------------------
/train_ant_syn_net.py:
--------------------------------------------------------------------------------
  1 | from __future__ import print_function
  2 | import argparse
  3 | from collections import OrderedDict
  4 | import sys
  5 | import time
  6 | import numpy
  7 | import theano
  8 | from theano import config
  9 | import theano.tensor as tensor
 10 | from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
 11 | from sklearn.metrics import precision_recall_fscore_support
 12 | import common
 13 | 
 14 | SEED = 123089 # Could change to any number
 15 | numpy.random.seed(SEED)
 16 | 
 17 | def main():
 18 |     """
 19 |     AntSynNET model
 20 |     Usage:
 21 |         python train_ant_syn_net.py -corpus <corpus_prefix> -data <dataset_prefix> -emb <embeddings_file>
 22 |                                     -model <model_name> -iter <iteration>
 23 |     <corpus_prefix>: the prefix of corpus
 24 |     <dataset_prefix>: the prefix of dataset
 25 |     <embeddings_file>: the embeddings file
 26 |     <model_name>: 1 for training combined model or 0 for training pattern-based model
 27 |     <iteration>: the number of iteration
 28 |     """
 29 |     parser = argparse.ArgumentParser()
 30 |     parser.add_argument('-corpus', type=str)
 31 |     parser.add_argument('-data', type=str)
 32 |     parser.add_argument('-emb', action='store', default=None, dest='emb_file')
 33 |     parser.add_argument('-model', type=int, default=1)
 34 |     parser.add_argument('-iter', type=int)
 35 |     args = parser.parse_args()
 36 |     # See AntSynNET function for all possible parameters and their definitions.
 37 |     AntSynNET(corpus_prefix=args.corpus, 
 38 |               dataset_prefix=args.data,
 39 |               embeddings_file=args.emb_file,
 40 |               model=args.model,
 41 |               epochs=args.iter)
 42 | 
 43 | def numpy_floatX(data):
 44 |     return numpy.asarray(data, dtype=config.floatX)
 45 | 
 46 | def zipp(params, tparams):
 47 |     """
 48 |     When we reload the model. Needed for the GPU stuff.
 49 |     """
 50 |     for kk, vv in params.items():
 51 |         tparams[kk].set_value(vv)
 52 | 
 53 | def unzip(zipped):
 54 |     """
 55 |     When we pickle the model. Needed for the GPU stuff.
 56 |     """
 57 |     new_params = OrderedDict()
 58 |     for kk, vv in zipped.items():
 59 |         new_params[kk] = vv.get_value()
 60 |     return new_params
 61 | 
 62 | def dropout_layer(state_before, use_noise, trng):
 63 |     proj = tensor.switch(use_noise,
 64 |                          (state_before *
 65 |                           trng.binomial(state_before.shape,
 66 |                                         p=0.5, n=1,
 67 |                                         dtype=state_before.dtype)),
 68 |                          state_before * 0.5)
 69 |     return proj
 70 | 
 71 | def _p(pp, name):
 72 |     return '%s_%s' % (pp, name)
 73 | 
 74 | def init_params(options, w2v=None):
 75 |     """
 76 |     Global (not LSTM) parameter. For the embeding and the classifier.
 77 |     """
 78 |     params = OrderedDict()
 79 |     # embedding
 80 |     if w2v is None:
 81 |         randn_lemma = numpy.random.rand(options['n_words'],
 82 |                               options['dim_lemma'])
 83 |         params['Wemb'] = (0.01 * randn_lemma).astype(config.floatX)
 84 |     else:
 85 |         params['Wemb'] = w2v.astype(config.floatX)
 86 |         
 87 |     randn_pos = numpy.random.rand(options['n_pos'],
 88 |                               options['dim_pos'])
 89 |     params['POS'] = (0.01 * randn_pos).astype(config.floatX)
 90 |     
 91 |     randn_dep = numpy.random.rand(options['n_dep'],
 92 |                               options['dim_dep'])
 93 |     params['DEP'] = (0.01 * randn_dep).astype(config.floatX)
 94 |     
 95 |     randn_dist = numpy.random.rand(options['n_dist'],
 96 |                               options['dim_dist'])
 97 |     params['DIST'] = (0.01 * randn_dist).astype(config.floatX)
 98 |         
 99 |     params = get_layer(options['encoder'])[0](options,
100 |                                               params,
101 |                                               prefix=options['encoder'])
102 |     # classifier
103 |     params['U'] = 0.01 * numpy.random.randn(options['dim_classifier'],
104 |                                             options['ydim']).astype(config.floatX)
105 |     params['b'] = numpy.zeros((options['ydim'],)).astype(config.floatX)
106 | 
107 |     return params
108 | 
109 | def load_params(path, params):
110 |     pp = numpy.load(path)
111 |     for kk, vv in params.items():
112 |         if kk not in pp:
113 |             raise Warning('%s is not in the archive' % kk)
114 |         params[kk] = pp[kk]
115 | 
116 |     return params
117 | 
118 | def get_layer(name):
119 |     fns = layers[name]
120 |     return fns
121 | 
122 | def init_tparams(params, ):
123 |     tparams = OrderedDict()
124 |     for kk, pp in params.items():
125 |         tparams[kk] = theano.shared(params[kk], name=kk)
126 |     return tparams
127 | 
128 | def ortho_weight(ndim):
129 |     W = numpy.random.randn(ndim, ndim)
130 |     u, s, v = numpy.linalg.svd(W)
131 |     return u.astype(config.floatX)
132 | 
133 | def param_init_lstm(options, params, prefix='lstm'):
134 |     """
135 |     Init the LSTM parameter:
136 | 
137 |     :see: init_params
138 |     """
139 |     W = numpy.concatenate([ortho_weight(options['dim_proj']),
140 |                            ortho_weight(options['dim_proj']),
141 |                            ortho_weight(options['dim_proj']),
142 |                            ortho_weight(options['dim_proj'])], axis=1)
143 |     params[_p(prefix, 'W')] = W
144 |     U = numpy.concatenate([ortho_weight(options['dim_proj']),
145 |                            ortho_weight(options['dim_proj']),
146 |                            ortho_weight(options['dim_proj']),
147 |                            ortho_weight(options['dim_proj'])], axis=1)
148 |     params[_p(prefix, 'U')] = U
149 |     b = numpy.zeros((4 * options['dim_proj'],))
150 |     params[_p(prefix, 'b')] = b.astype(config.floatX)
151 | 
152 |     return params
153 | 
154 | 
155 | def lstm_layer(tparams, state_below, options, prefix='lstm', mask=None):
156 |     nsteps = state_below.shape[0]
157 |     if state_below.ndim == 3:
158 |         n_samples = state_below.shape[1]
159 |     else:
160 |         n_samples = 1
161 | 
162 |     assert mask is not None
163 | 
164 |     def _slice(_x, n, dim):
165 |         if _x.ndim == 3:
166 |             return _x[:, :, n * dim:(n + 1) * dim]
167 |         return _x[:, n * dim:(n + 1) * dim]
168 | 
169 |     def _step(m_, x_, h_, c_):
170 |         preact = tensor.dot(h_, tparams[_p(prefix, 'U')])
171 |         preact += x_
172 | 
173 |         i = tensor.nnet.sigmoid(_slice(preact, 0, options['dim_proj']))
174 |         f = tensor.nnet.sigmoid(_slice(preact, 1, options['dim_proj']))
175 |         o = tensor.nnet.sigmoid(_slice(preact, 2, options['dim_proj']))
176 |         c = tensor.tanh(_slice(preact, 3, options['dim_proj']))
177 | 
178 |         c = f * c_ + i * c
179 |         c = m_[:, None] * c + (1. - m_)[:, None] * c_
180 | 
181 |         h = o * tensor.tanh(c)
182 |         h = m_[:, None] * h + (1. - m_)[:, None] * h_
183 | 
184 |         return h, c
185 | 
186 |     state_below = (tensor.dot(state_below, tparams[_p(prefix, 'W')]) +
187 |                    tparams[_p(prefix, 'b')])
188 | 
189 |     dim_proj = options['dim_proj']
190 |     rval, updates = theano.scan(_step,
191 |                                 sequences=[mask, state_below],
192 |                                 outputs_info=[tensor.alloc(numpy_floatX(0.),
193 |                                                            n_samples,
194 |                                                            dim_proj),
195 |                                               tensor.alloc(numpy_floatX(0.),
196 |                                                            n_samples,
197 |                                                            dim_proj)],
198 |                                 name=_p(prefix, '_layers'),
199 |                                 n_steps=nsteps)
200 |     return rval[0][-1]
201 | 
202 | layers = {'lstm': (param_init_lstm, lstm_layer)}
203 | 
204 | def sgd(lr, tparams, grads, x, mask, y, cost):
205 |     """ Stochastic Gradient Descent
206 | 
207 |     :note: A more complicated version of sgd then needed.  This is
208 |         done like that for adadelta and rmsprop.
209 | 
210 |     """
211 |     # New set of shared variable that will contain the gradient
212 |     # for a mini-batch.
213 |     gshared = [theano.shared(p.get_value() * 0., name='%s_grad' % k)
214 |                for k, p in tparams.items()]
215 |     gsup = [(gs, g) for gs, g in zip(gshared, grads)]
216 | 
217 |     # Function that computes gradients for a mini-batch, but do not
218 |     # updates the weights.
219 |     grad_updates = gsup
220 | 
221 |     pup = [(p, p - lr * g) for p, g in zip(tparams.values(), gshared)]
222 | 
223 |     # Function that updates the weights from the previously computed
224 |     # gradient.
225 |     params_updates = pup
226 | 
227 |     return grad_updates, params_updates
228 | 
229 | def adadelta(lr, tparams, grads):
230 |     """
231 |     An adaptive learning rate optimizer
232 | 
233 |     Parameters
234 |     ----------
235 |     lr : Theano SharedVariable
236 |         Initial learning rate
237 |     tpramas: Theano SharedVariable
238 |         Model parameters
239 |     grads: Theano variable
240 |         Gradients of cost w.r.t to parameres
241 |     x: Theano variable
242 |         Model inputs
243 |     mask: Theano variable
244 |         Sequence mask
245 |     y: Theano variable
246 |         Targets
247 |     cost: Theano variable
248 |         Objective fucntion to minimize
249 | 
250 |     Notes
251 |     -----
252 |     For more information, see [ADADELTA]_.
253 | 
254 |     .. [ADADELTA] Matthew D. Zeiler, *ADADELTA: An Adaptive Learning
255 |        Rate Method*, arXiv:1212.5701.
256 |     """
257 | 
258 |     zipped_grads = [theano.shared(p.get_value() * numpy_floatX(0.),
259 |                                   name='%s_grad' % k)
260 |                     for k, p in tparams.items()]
261 |     running_up2 = [theano.shared(p.get_value() * numpy_floatX(0.),
262 |                                  name='%s_rup2' % k)
263 |                    for k, p in tparams.items()]
264 |     running_grads2 = [theano.shared(p.get_value() * numpy_floatX(0.),
265 |                                     name='%s_rgrad2' % k)
266 |                       for k, p in tparams.items()]
267 | 
268 |     zgup = [(zg, g) for zg, g in zip(zipped_grads, grads)]
269 |     rg2up = [(rg2, 0.95 * rg2 + 0.05 * (g ** 2))
270 |              for rg2, g in zip(running_grads2, grads)]
271 | 
272 |     grad_updates=zgup + rg2up
273 |     
274 |     updir = [-tensor.sqrt(ru2 + 1e-6) / tensor.sqrt(rg2 + 1e-6) * zg
275 |              for zg, ru2, rg2 in zip(zipped_grads,
276 |                                      running_up2,
277 |                                      running_grads2)]
278 |     ru2up = [(ru2, 0.95 * ru2 + 0.05 * (ud ** 2))
279 |              for ru2, ud in zip(running_up2, updir)]
280 |     param_up = [(p, p + ud) for p, ud in zip(tparams.values(), updir)]
281 | 
282 |     params_updates = ru2up + param_up
283 | 
284 |     return grad_updates, params_updates
285 | 
286 | def rmsprop(lr, tparams, grads):
287 |     """
288 |     A variant of  SGD that scales the step size by running average of the
289 |     recent step norms.
290 | 
291 |     Parameters
292 |     ----------
293 |     lr : Theano SharedVariable
294 |         Initial learning rate
295 |     tpramas: Theano SharedVariable
296 |         Model parameters
297 |     grads: Theano variable
298 |         Gradients of cost w.r.t to parameres
299 |     x: Theano variable
300 |         Model inputs
301 |     mask: Theano variable
302 |         Sequence mask
303 |     y: Theano variable
304 |         Targets
305 |     cost: Theano variable
306 |         Objective fucntion to minimize
307 | 
308 |     Notes
309 |     -----
310 |     For more information, see [Hint2014]_.
311 | 
312 |     .. [Hint2014] Geoff Hinton, *Neural Networks for Machine Learning*,
313 |        lecture 6a,
314 |        http://cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf
315 |     """
316 | 
317 |     zipped_grads = [theano.shared(p.get_value() * numpy_floatX(0.),
318 |                                   name='%s_grad' % k)
319 |                     for k, p in tparams.items()]
320 |     running_grads = [theano.shared(p.get_value() * numpy_floatX(0.),
321 |                                    name='%s_rgrad' % k)
322 |                      for k, p in tparams.items()]
323 |     running_grads2 = [theano.shared(p.get_value() * numpy_floatX(0.),
324 |                                     name='%s_rgrad2' % k)
325 |                       for k, p in tparams.items()]
326 | 
327 |     zgup = [(zg, g) for zg, g in zip(zipped_grads, grads)]
328 |     rgup = [(rg, 0.95 * rg + 0.05 * g) for rg, g in zip(running_grads, grads)]
329 |     rg2up = [(rg2, 0.95 * rg2 + 0.05 * (g ** 2))
330 |              for rg2, g in zip(running_grads2, grads)]
331 | 
332 |     grad_updates = zgup + rgup + rg2up
333 | 
334 |     updir = [theano.shared(p.get_value() * numpy_floatX(0.),
335 |                            name='%s_updir' % k)
336 |              for k, p in tparams.items()]
337 |     updir_new = [(ud, 0.9 * ud - 1e-4 * zg / tensor.sqrt(rg2 - rg ** 2 + 1e-4))
338 |                  for ud, zg, rg, rg2 in zip(updir, zipped_grads, running_grads,
339 |                                             running_grads2)]
340 |     param_up = [(p, p + udn[1])
341 |                 for p, udn in zip(tparams.values(), updir_new)]
342 |     
343 |     params_updates = updir_new + param_up
344 | 
345 |     return grad_updates, params_updates
346 | 
347 | def pred_error(f_pred, preprocess_data, data, iterator, pair_vectors=None):
348 |     """
349 |     Just compute the error
350 |     f_pred: Theano fct computing the prediction
351 |     preprocess_data: usual preprocess_data for that dataset.
352 |     """
353 |     preds = []
354 |     targets = []
355 |     for valid_index in iterator:
356 |         l, p, g, d, mask, c = preprocess_data(data[0][valid_index])
357 |         if pair_vectors is not None:
358 |             source_term, target_term = pair_vectors[valid_index]
359 |             pred = f_pred(l, p, g, d, mask, c, source_term, target_term)
360 |         else:
361 |             pred = f_pred(l, p, g, d, mask, c)
362 |         preds.extend(pred)
363 |         targets.append(data[1][valid_index])
364 |            
365 |     preds = numpy.array(preds)
366 |     targets = numpy.array(targets)  
367 |     valid_err = (preds == targets).sum()
368 |     
369 |     valid_err = 1. - numpy_floatX(valid_err) / len(data[0])
370 | 
371 |     return valid_err
372 | 
373 | def predict(f_pred, preprocess_data, data, iterator, pair_vectors=None):
374 |     preds = []
375 |     targets = []
376 |     for valid_index in iterator:
377 |         l, p, g, d, mask, c = preprocess_data(data[0][valid_index])
378 |         if pair_vectors is not None:
379 |             source_term, target_term = pair_vectors[valid_index]
380 |             pred = f_pred(l, p, g, d, mask, c, source_term, target_term)
381 |         else:
382 |             pred = f_pred(l, p, g, d, mask, c)
383 |         preds.extend(pred)
384 |         targets.append(data[1][valid_index])
385 |         
386 |     return preds, targets
387 | 
388 | def AntSynNET(
389 |     corpus_prefix, # The prefix of corpus.
390 |     dataset_prefix, # The prefix of dataset.
391 |     embeddings_file=None, # File of pre-trained word embeddings.
392 |     model=1, # 1 for training combined model or 0 for training pattern-based model.
393 |     dim_lemma=100, # The number dimension of lemma.
394 |     dim_pos=10, # The number dimension of POS.
395 |     dim_dep=10, # The number dimension of dependency label.
396 |     dim_dist=10, # The number dimension of distance label.
397 |     epochs=40,  # The maximum number of epoch to run
398 |     dispFreq=1000,  # Display to stdout the training progress every N updates
399 |     decay_c=0.,  # Weight decay for the classifier applied to the U weights.
400 |     optimizer=adadelta,  # sgd, adadelta and rmsprop available, sgd very hard to use, not recommended (probably need momentum and decaying learning rate).
401 |     encoder='lstm',  # TODO: can be removed must be lstm.
402 |     save_model='AntSynNET_model.npz',  # The parameters of model will be saved there
403 |     maxlen=12,  # Sequence longer then this get ignored
404 |     lrate=0.0001, # Learning rate for sgd (not used for adadelta and rmsprop)
405 |     noise_std=0.5, # Dropout rate
406 |     use_dropout=True,  # if False slightly faster, but worst test error
407 |     reload_model=None,  # Path to a saved model we want to start from.
408 | ):
409 |     
410 |     # Model options
411 |     model_options = locals().copy()
412 | 
413 |     load_data, preprocess_instance = common.load_data, common.preprocess_instance
414 | 
415 |     # Loads data
416 |     pre_trained_vecs, train, valid, test, keys, lemma_dict, pos_dict, dep_dict, dist_dict = \
417 |         load_data(corpus_prefix, dataset_prefix, embeddings_file)
418 |         
419 |     X_train, y_train = train
420 |     X_test, y_test = test
421 |     X_valid, y_valid = valid
422 |     
423 |     train_key_pairs, test_key_pairs, valid_key_pairs = keys
424 |     
425 |     kf_valid = numpy.random.permutation(len(X_valid))
426 |     kf_test = numpy.random.permutation(len(X_test))
427 | 
428 |     print("%d train examples" % len(y_train))
429 |     print("%d valid examples" % len(y_valid))
430 |     print("%d test examples" % len(y_test))
431 |         
432 |     ydim = numpy.max(train[1]) + 1
433 |     model_options['n_words'] = len(lemma_dict)
434 |     model_options['n_pos'] = len(pos_dict)
435 |     model_options['n_dep'] = len(dep_dict)
436 |     model_options['n_dist'] = len(dist_dict)
437 |     
438 |     if pre_trained_vecs is not None:
439 |         model_options['dim_lemma'] = len(pre_trained_vecs[0])
440 |         
441 |     model_options['dim_proj'] = model_options['dim_lemma'] + dim_pos + dim_dep + dim_dist
442 |     
443 |     if model_options['model']==1:
444 |         model_options['dim_classifier'] = 2 * model_options['dim_lemma'] + model_options['dim_proj']
445 |     elif model_options['model']==0:
446 |         model_options['dim_classifier'] = model_options['dim_proj']
447 |     else:
448 |         print('1 for training combined model or 0 for training pattern-based model')
449 |         
450 |     model_options['ydim'] = ydim
451 |     
452 |     print("model options", model_options)
453 | 
454 |     print('Building model')
455 |     # This create the initial parameters as numpy ndarrays.
456 |     # Dict name (string) -> numpy ndarray
457 |     params = init_params(model_options, pre_trained_vecs)
458 | 
459 |     if reload_model is not None:
460 |         load_params(reload_model, params)
461 | 
462 |     # This create Theano Shared Variable from the parameters.
463 |     # Dict name (string) -> Theano Tensor Shared Variable
464 |     # params and tparams have different copy of the weights.
465 |     tparams = init_tparams(params)
466 |     
467 |     trng = RandomStreams(SEED)
468 |     use_noise = theano.shared(numpy_floatX(0.))
469 | 
470 |     l = tensor.matrix('lemma', dtype='int64')
471 |     p = tensor.matrix('pos', dtype='int64')
472 |     g = tensor.matrix('dep', dtype='int64')
473 |     d = tensor.matrix('dist', dtype='int64')
474 |     mask = tensor.matrix('mask', dtype=config.floatX)
475 |     c = tensor.matrix('freq', dtype='int64')
476 |     y = tensor.vector('y', dtype='int64')
477 |     lr = tensor.scalar(name='lr')
478 |     
479 |     if model_options['model']==1:
480 |         s_term = tensor.scalar('source term', dtype='int64')
481 |         t_term = tensor.scalar('target term', dtype='int64')
482 | 
483 |     zero_vec_lemma = tensor.vector()
484 |     zero_vec_pos = tensor.vector()
485 |     zero_vec_dep = tensor.vector()
486 |     zero_vec_dist = tensor.vector()
487 |     zero_lemma = numpy.zeros(model_options['dim_lemma'])
488 |     zero_pos = numpy.zeros(model_options['dim_pos'])
489 |     zero_dep = numpy.zeros(model_options['dim_dep'])
490 |     zero_dist = numpy.zeros(model_options['dim_dist'])    
491 |     
492 |     n_timesteps = l.shape[0]
493 |     n_samples = l.shape[1]
494 |     
495 |     lemma = tparams['Wemb'][l.flatten()].reshape([n_timesteps, n_samples, model_options['dim_lemma']])
496 |     pos = tparams['POS'][p.flatten()].reshape([n_timesteps, n_samples, model_options['dim_pos']])
497 |     dep = tparams['DEP'][g.flatten()].reshape([n_timesteps, n_samples, model_options['dim_dep']])
498 |     dist = tparams['DIST'][d.flatten()].reshape([n_timesteps, n_samples, model_options['dim_dist']])
499 | 
500 |     if model_options['use_dropout']:
501 |         lemma = dropout_layer(lemma, use_noise, trng)
502 |         pos = dropout_layer(pos, use_noise, trng)
503 |         dep = dropout_layer(dep, use_noise, trng)
504 |         dist = dropout_layer(dist, use_noise, trng)
505 |  
506 |     emb = tensor.concatenate([lemma,pos,dep,dist], axis=2)
507 |     
508 |     proj = get_layer(model_options['encoder'])[1](tparams, emb, model_options,
509 |                                                   prefix=model_options['encoder'], mask=mask)
510 | 
511 |     if model_options['use_dropout']:
512 |         proj = dropout_layer(proj, use_noise, trng)
513 | 
514 |     proj = tensor.dot(tensor.cast(c, 'float32'), proj)
515 |     proj = tensor.sum(proj,axis=0) / tensor.sum(c).astype(config.floatX)
516 |     
517 |     if model_options['model']==1:
518 |         source_term_emb = tparams['Wemb'][s_term]
519 |         target_term_emb = tparams['Wemb'][t_term]
520 |         proj = tensor.concatenate([source_term_emb, proj, target_term_emb])
521 |         
522 |     pred = tensor.nnet.softmax(tensor.dot(proj, tparams['U']) + tparams['b'])
523 |     if model_options['model']==1:
524 |         f_pred_prob = theano.function([l, p, g, d, mask, c, s_term, t_term], pred, 
525 |                                       name='f_pred_prob', on_unused_input='ignore')
526 |         f_pred = theano.function([l, p, g, d, mask, c, s_term, t_term], pred.argmax(axis=1), 
527 |                                  name='f_pred', on_unused_input='ignore')
528 |     else:
529 |         f_pred_prob = theano.function([l, p, g, d, mask, c], pred, 
530 |                                       name='f_pred_prob', on_unused_input='ignore')
531 |         f_pred = theano.function([l, p, g, d, mask, c], pred.argmax(axis=1), 
532 |                                  name='f_pred', on_unused_input='ignore')
533 |     
534 |     off = 1e-8
535 |     if pred.dtype == 'float16':
536 |         off = 1e-6
537 |     #n_samples = 1 corresponding to batch-size = 1
538 |     cost = -tensor.log(pred[tensor.arange(1), y] + off).mean()
539 |     
540 |     if decay_c > 0.:
541 |         decay_c = theano.shared(numpy_floatX(decay_c), name='decay_c')
542 |         weight_decay = 0.
543 |         weight_decay += (tparams['U'] ** 2).sum()
544 |         weight_decay *= decay_c
545 |         cost += weight_decay
546 |     
547 |     grads = tensor.grad(cost, wrt=list(tparams.values()))
548 |     
549 |     grad_updates, params_updates = optimizer(lr, tparams, grads)
550 |     
551 |     if model_options['model']==1:    
552 |         f_grad_shared = theano.function([l, p, g, d, mask, c, s_term, t_term, y], cost, updates=grad_updates,
553 |                                     name='adadelta_f_grad_shared', on_unused_input='ignore')
554 |     else:
555 |         f_grad_shared = theano.function([l, p, g, d, mask, c, y], cost, updates=grad_updates,
556 |                                     name='adadelta_f_grad_shared', on_unused_input='ignore')
557 |         
558 |     f_update = theano.function([lr], [], updates=params_updates, on_unused_input='ignore',
559 |                                 name='adadelta_f_update')
560 |     
561 |     set_zero_lemma = theano.function([zero_vec_lemma], 
562 |                                      updates=[(tparams['Wemb'], tensor.set_subtensor(tparams['Wemb'][0,:], zero_vec_lemma))],
563 |                                      allow_input_downcast=True)
564 |     set_zero_pos = theano.function([zero_vec_pos], 
565 |                                    updates=[(tparams['POS'], tensor.set_subtensor(tparams['POS'][0,:], zero_vec_pos))],
566 |                                    allow_input_downcast=True)
567 |     set_zero_dep = theano.function([zero_vec_dep], 
568 |                                    updates=[(tparams['DEP'], tensor.set_subtensor(tparams['DEP'][0,:], zero_vec_dep))],
569 |                                    allow_input_downcast=True) 
570 |     set_zero_dist = theano.function([zero_vec_dist], 
571 |                                     updates=[(tparams['DIST'], tensor.set_subtensor(tparams['DIST'][0,:], zero_vec_dist))],
572 |                                     allow_input_downcast=True) 
573 |     
574 |     print('Training.......')
575 |         
576 |     uidx = 0  # the number of update done
577 |     start_time = time.time()
578 |     try:
579 |         for eidx in range(epochs):
580 |             n_samples = 0
581 |             dispLoss = 0.
582 |             # Get new shuffled index for the training set.
583 |             kf_train = numpy.random.permutation(len(X_train))
584 |                 
585 |             for train_idx in kf_train:
586 |                 instance = X_train[train_idx]
587 |                 l, p, g, d, mask, c = preprocess_instance(instance)
588 |                 source_term, target_term = train_key_pairs[train_idx]
589 |                 label = [y_train[train_idx]]
590 |                 
591 |                 uidx += 1
592 |                 use_noise.set_value(noise_std)
593 |                 
594 |                 if model_options['model']==1:
595 |                     cost = f_grad_shared(l, p, g, d, mask, c, source_term, target_term, label)
596 |                 else:
597 |                     cost = f_grad_shared(l, p, g, d, mask, c, label)
598 |                     
599 |                 f_update(lrate)
600 | 
601 |                 set_zero_lemma(zero_lemma)
602 |                 set_zero_pos(zero_pos)
603 |                 set_zero_dep(zero_dep)
604 |                 set_zero_dist(zero_dist)
605 |                                                           
606 |                 dispLoss += cost
607 |                 n_samples += 1
608 | 
609 |                 if numpy.mod(uidx, dispFreq) == 0:
610 |                     cost = dispLoss / n_samples
611 |                     use_noise.set_value(0.)
612 |                     if model_options['model']==1:
613 |                         valid_err = pred_error(f_pred, preprocess_instance, valid, kf_valid, valid_key_pairs)
614 |                     else:
615 |                         valid_err = pred_error(f_pred, preprocess_instance, valid, kf_valid)
616 |                     print('Epoch: %d, Update: %d, Cost: %f, Valid: %.3f' %(eidx, uidx, cost, valid_err))
617 |                     
618 |             print('Seen %d samples' % n_samples)
619 | 
620 |     except KeyboardInterrupt:
621 |         print("Training interupted")
622 |         
623 |     use_noise.set_value(0.)
624 |     if model_options['model']==1:
625 |         preds, targets = predict(f_pred, preprocess_instance, test, kf_test, test_key_pairs) 
626 |     else:
627 |         preds, targets = predict(f_pred, preprocess_instance, test, kf_test)
628 |         
629 |     p, r, f1, _ = precision_recall_fscore_support(targets, preds, average='binary')
630 |     print ('Precision: %.3f, Recall: %.3f, F1: %.3f' % (p, r, f1))
631 |     
632 |     save_params = unzip(tparams)
633 |     if save_model is not None:
634 |         numpy.savez(save_model, preds=preds, targets=targets, p=p, r=r, f1=f1, **save_params)
635 |     
636 |     end_time = time.time()
637 |     
638 |     print('The code run for %d epochs, with %f sec/epochs' % (
639 |         (eidx + 1), (end_time - start_time) / (1. * (eidx + 1))))
640 |     print( ('Training took %.1fs' %
641 |             (end_time - start_time)), file=sys.stderr)
642 |     return p, r, f1
643 | 
644 | if __name__ == '__main__':
645 |     main()
646 | 
647 | 


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