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* Moving tagger to accept multiple correct answers

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Matthew Honnibal 2014-11-09 15:18:33 +11:00
parent 10a33ec725
commit 602f993af9
2 changed files with 12 additions and 6 deletions
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2
spacy/tagger.pxd
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@ -18,7 +18,7 @@ cpdef enum TagType:
cdef class Tagger:
cpdef int set_tags(self, Tokens tokens) except -1
cpdef class_t predict(self, int i, Tokens tokens) except 0
cpdef int tell_answer(self, class_t gold) except -1
cpdef int tell_answer(self, list gold) except -1
cpdef readonly Pool mem
cpdef readonly Extractor extractor

16
spacy/tagger.pyx
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@ -45,7 +45,7 @@ def train(train_sents, model_dir, nr_iter=10):
guess = tagger.predict(i, tokens)
tokens.set_tag(i, tagger.tag_type, guess)
if gold != NULL_TAG:
tagger.tell_answer(gold)
tagger.tell_answer([gold])
total += 1
n_corr += guess == gold
#print('%s\t%d\t%d' % (tokens[i].string, guess, gold))
@ -116,7 +116,7 @@ cdef class Tagger:
self._guess = self.model.score(self._scores, self._feats, self._values)
return self._guess
cpdef int tell_answer(self, class_t gold) except -1:
cpdef int tell_answer(self, list golds) except -1:
"""Provide the correct tag for the word the tagger was last asked to predict.
During Tagger.predict, the tagger remembers the features and prediction
for the example. These are used to calculate a weight update given the
@ -130,11 +130,17 @@ cdef class Tagger:
>>> EN.pos_tagger.tell_answer(JJ)
"""
cdef class_t guess = self._guess
if gold == guess or gold == NULL_TAG:
if guess in golds:
self.model.update({})
return 0
counts = {guess: {}, gold: {}}
self.extractor.count(counts[gold], self._feats, 1)
best_gold = golds[0]
best_score = self._scores[best_gold-1]
for gold in golds[1:]:
if self._scores[gold-1] > best_gold:
best_score = self._scores[best_gold-1]
best_gold = gold
counts = {guess: {}, best_gold: {}}
self.extractor.count(counts[best_gold], self._feats, 1)
self.extractor.count(counts[guess], self._feats, -1)
self.model.update(counts)