1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
|
#!/usr/bin/env python
import collections, sys
import cdec.configobj
CAT = '[X]' # Default non-terminal
MAX_SIZE = 15 # Max span of a grammar rule (source)
MAX_LEN = 5 # Max number of terminals and non-terminals in a rule (source)
MAX_NT = 2 # Max number of non-terminals in a rule
MIN_GAP = 1 # Min number of terminals between non-terminals (source)
# Spans are _inclusive_ on both ends [i, j]
# TODO: Replace all of this with bit vectors?
def span_check(vec, i, j):
k = i
while k <= j:
if vec[k]:
return False
k += 1
return True
def span_flip(vec, i, j):
k = i
while k <= j:
vec[k] = ~vec[k]
k += 1
# Next non-terminal
def next_nt(nt):
if not nt:
return 1
return nt[-1][0] + 1
class NonTerminal:
def __init__(self, index):
self.index = index
def __str__(self):
return '[X,{0}]'.format(self.index)
def fmt_rule(f_sym, e_sym, links):
a_str = ' '.join('{0}-{1}'.format(i, j) for (i, j) in links)
return '[X] ||| {0} ||| {1} ||| {2}'.format(' '.join(str(sym) for sym in f_sym),
' '.join(str(sym) for sym in e_sym),
a_str)
class OnlineGrammarExtractor:
def __init__(self, config=None):
if isinstance(config, str) or isinstance(config, unicode):
if not os.path.exists(config):
raise IOError('cannot read configuration from {0}'.format(config))
config = cdec.configobj.ConfigObj(config, unrepr=True)
elif not config:
config = collections.defaultdict(lambda: None)
self.category = CAT
self.max_size = MAX_SIZE
self.max_length = config['max_len'] or MAX_LEN
self.max_nonterminals = config['max_nt'] or MAX_NT
self.min_gap_size = MIN_GAP
# Hard coded: require at least one aligned word
# Hard coded: require tight phrases
# Phrase counts
self.phrases_f = collections.defaultdict(lambda: 0)
self.phrases_e = collections.defaultdict(lambda: 0)
self.phrases_fe = collections.defaultdict(lambda: collections.defaultdict(lambda: 0))
# Bilexical counts
self.bilex_f = collections.defaultdict(lambda: 0)
self.bilex_e = collections.defaultdict(lambda: 0)
self.bilex_fe = collections.defaultdict(lambda: collections.defaultdict(lambda: 0))
# Aggregate bilexical counts
def aggr_bilex(self, f_words, e_words):
for e_w in e_words:
self.bilex_e[e_w] += 1
for f_w in f_words:
self.bilex_f[f_w] += 1
for e_w in e_words:
self.bilex_fe[f_w][e_w] += 1
# Aggregate stats from a training instance:
# Extract hierarchical phrase pairs
# Update bilexical counts
def add_instance(self, f_words, e_words, alignment):
# Bilexical counts
self.aggr_bilex(f_words, e_words)
# Phrase pairs extracted from this instance
phrases = set()
f_len = len(f_words)
# Pre-compute alignment info
al = [[] for i in range(f_len)]
al_span = [[f_len + 1, -1] for i in range(f_len)]
for (f, e) in alignment:
al[f].append(e)
al_span[f][0] = min(al_span[f][0], e)
al_span[f][1] = max(al_span[f][1], e)
# Target side word coverage
# TODO: Does Cython do bit vectors?
cover = [0] * f_len
# Extract all possible hierarchical phrases starting at a source index
# f_ i and j are current, e_ i and j are previous
def extract(f_i, f_j, e_i, e_j, wc, links, nt, nt_open):
# Phrase extraction limits
if wc > self.max_length or (f_j + 1) > f_len or \
(f_j - f_i) + 1 > self.max_size:
return
# Unaligned word
if not al[f_j]:
# Open non-terminal: extend
if nt_open:
nt[-1][2] += 1
extract(f_i, f_j + 1, e_i, e_j, wc, links, nt, True)
nt[-1][2] -= 1
# No open non-terminal: extend with word
else:
extract(f_i, f_j + 1, e_i, e_j, wc + 1, links, nt, False)
return
# Aligned word
link_i = al_span[f_j][0]
link_j = al_span[f_j][1]
new_e_i = min(link_i, e_i)
new_e_j = max(link_j, e_j)
# Open non-terminal: close, extract, extend
if nt_open:
# Close non-terminal, checking for collisions
old_last_nt = nt[-1][:]
nt[-1][2] = f_j
if link_i < nt[-1][3]:
if not span_check(cover, link_i, nt[-1][3] - 1):
nt[-1] = old_last_nt
return
span_flip(cover, link_i, nt[-1][3] - 1)
nt[-1][3] = link_i
if link_j > nt[-1][4]:
if not span_check(cover, nt[-1][4] + 1, link_j):
nt[-1] = old_last_nt
return
span_flip(cover, nt[-1][4] + 1, link_j)
nt[-1][4] = link_j
for rule in self.form_rules(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links):
phrases.add(rule)
extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False)
nt[-1] = old_last_nt
if link_i < nt[-1][3]:
span_flip(cover, link_i, nt[-1][3] - 1)
if link_j > nt[-1][4]:
span_flip(cover, nt[-1][4] + 1, link_j)
return
# No open non-terminal
# Extract, extend with word
collision = False
for link in al[f_j]:
if cover[link]:
collision = True
# Collisions block extraction and extension, but may be okay for
# continuing non-terminals
if not collision:
plus_links = []
for link in al[f_j]:
plus_links.append((f_j, link))
cover[link] = ~cover[link]
links.append(plus_links)
for rule in self.form_rules(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links):
phrases.add(rule)
extract(f_i, f_j + 1, new_e_i, new_e_j, wc + 1, links, nt, False)
links.pop()
for link in al[f_j]:
cover[link] = ~cover[link]
# Try to add a word to a (closed) non-terminal, extract, extend
if nt and nt[-1][2] == f_j - 1:
# Add to non-terminal, checking for collisions
old_last_nt = nt[-1][:]
nt[-1][2] = f_j
if link_i < nt[-1][3]:
if not span_check(cover, link_i, nt[-1][3] - 1):
nt[-1] = old_last_nt
return
span_flip(cover, link_i, nt[-1][3] - 1)
nt[-1][3] = link_i
if link_j > nt[-1][4]:
if not span_check(cover, nt[-1][4] + 1, link_j):
nt[-1] = old_last_nt
return
span_flip(cover, nt[-1][4] + 1, link_j)
nt[-1][4] = link_j
# Require at least one word in phrase
if links:
for rule in self.form_rules(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links):
phrases.add(rule)
extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False)
nt[-1] = old_last_nt
if new_e_i < nt[-1][3]:
span_flip(cover, link_i, nt[-1][3] - 1)
if link_j > nt[-1][4]:
span_flip(cover, nt[-1][4] + 1, link_j)
# Try to start a new non-terminal, extract, extend
if (not nt or f_j - nt[-1][2] > 1) and len(nt) < self.max_nonterminals:
# Check for collisions
if not span_check(cover, link_i, link_j):
return
span_flip(cover, link_i, link_j)
nt.append([next_nt(nt), f_j, f_j, link_i, link_j])
# Require at least one word in phrase
if links:
for rule in self.form_rules(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links):
phrases.add(rule)
extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False)
nt.pop()
span_flip(cover, link_i, link_j)
# TODO: try adding NT to start, end, both
# check: one aligned word on boundary that is not part of a NT
# Try to extract phrases from every f index
f_i = 0
while f_i < f_len:
# Skip if phrases won't be tight on left side
if not al[f_i]:
f_i += 1
continue
extract(f_i, f_i, f_len + 1, -1, 1, [], [], False)
f_i += 1
for rule in sorted(phrases):
print rule
# Create a rule from source, target, non-terminals, and alignments
def form_rules(self, f_i, e_i, f_span, e_span, nt, al):
# This could be more efficient but is unlikely to be the bottleneck
rules = []
nt_inv = sorted(nt, cmp=lambda x, y: cmp(x[3], y[3]))
f_sym = f_span[:]
off = f_i
for next_nt in nt:
nt_len = (next_nt[2] - next_nt[1]) + 1
i = 0
while i < nt_len:
f_sym.pop(next_nt[1] - off)
i += 1
f_sym.insert(next_nt[1] - off, NonTerminal(next_nt[0]))
off += (nt_len - 1)
e_sym = e_span[:]
off = e_i
for next_nt in nt_inv:
nt_len = (next_nt[4] - next_nt[3]) + 1
i = 0
while i < nt_len:
e_sym.pop(next_nt[3] - off)
i += 1
e_sym.insert(next_nt[3] - off, NonTerminal(next_nt[0]))
off += (nt_len - 1)
# Adjusting alignment links takes some doing
links = [list(link) for sub in al for link in sub]
links_len = len(links)
nt_len = len(nt)
nt_i = 0
off = f_i
i = 0
while i < links_len:
while nt_i < nt_len and links[i][0] > nt[nt_i][1]:
off += (nt[nt_i][2] - nt[nt_i][1])
nt_i += 1
links[i][0] -= off
i += 1
nt_i = 0
off = e_i
i = 0
while i < links_len:
while nt_i < nt_len and links[i][1] > nt_inv[nt_i][3]:
off += (nt_inv[nt_i][4] - nt_inv[nt_i][3])
nt_i += 1
links[i][1] -= off
i += 1
# Rule
rules.append(fmt_rule(f_sym, e_sym, links))
if len(f_sym) >= self.max_length or len(nt) >= self.max_nonterminals:
return rules
last_index = nt[-1][0] if nt else 0
# Rule [X]
if not nt or not isinstance(f_sym[-1], NonTerminal):
f_sym.append(NonTerminal(last_index + 1))
e_sym.append(NonTerminal(last_index + 1))
rules.append(fmt_rule(f_sym, e_sym, links))
f_sym.pop()
e_sym.pop()
# [X] Rule
if not nt or not isinstance(f_sym[0], NonTerminal):
for sym in f_sym:
if isinstance(sym, NonTerminal):
sym.index += 1
for sym in e_sym:
if isinstance(sym, NonTerminal):
sym.index += 1
for link in links:
link[0] += 1
link[1] += 1
f_sym.insert(0, NonTerminal(1))
e_sym.insert(0, NonTerminal(1))
rules.append(fmt_rule(f_sym, e_sym, links))
if len(f_sym) >= self.max_length or len(nt) + 1 >= self.max_nonterminals:
return rules
# [X] Rule [X]
if not nt or not isinstance(f_sym[-1], NonTerminal):
f_sym.append(NonTerminal(last_index + 2))
e_sym.append(NonTerminal(last_index + 2))
rules.append(fmt_rule(f_sym, e_sym, links))
return rules
def main(argv):
extractor = OnlineGrammarExtractor()
for line in sys.stdin:
f_words, e_words, a_str = (x.split() for x in line.split('|||'))
alignment = sorted(tuple(int(y) for y in x.split('-')) for x in a_str)
extractor.add_instance(f_words, e_words, alignment)
if __name__ == '__main__':
main(sys.argv)
|