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Improve the API for the GoldParse class.

This commit is contained in:
Matthew Honnibal 2016-10-15 23:53:29 +02:00
parent e07fe92b27
commit a48aa15384
1 changed files with 24 additions and 21 deletions
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45
spacy/gold.pyx
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@ -216,7 +216,12 @@ def _consume_ent(tags):
cdef class GoldParse:
@classmethod
def new_init(cls, doc, annot_tuples=None, words=None, tags=None, heads=None,
def from_annot_tuples(cls, doc, annot_tuples, make_projective=False):
_, words, tags, heads, deps, entities = annot_tuples
return cls(doc, words=words, tags=tags, heads=heads, deps=deps, entities=entities,
make_projective=make_projective)
def __init__(cls, doc, annot_tuples=None, words=None, tags=None, heads=None,
deps=None, entities=None):
if words is None:
words = [token.text for token in doc]
@ -233,50 +238,48 @@ cdef class GoldParse:
elif not isinstance(entities[0], basestring):
# Assume we have entities specified by character offset.
entities = biluo_tags_from_offsets(doc, entities)
return cls(doc, [(range(len(doc)), words, tags, heads, deps, entities)])
def __init__(self, tokens, annot_tuples, make_projective=False):
self.mem = Pool()
self.loss = 0
self.length = len(tokens)
# These are filled by the tagger/parser/entity recogniser
self.c.tags = <int*>self.mem.alloc(len(tokens), sizeof(int))
self.c.heads = <int*>self.mem.alloc(len(tokens), sizeof(int))
self.c.labels = <int*>self.mem.alloc(len(tokens), sizeof(int))
self.c.ner = <Transition*>self.mem.alloc(len(tokens), sizeof(Transition))
self.c.tags = <int*>self.mem.alloc(len(doc), sizeof(int))
self.c.heads = <int*>self.mem.alloc(len(doc), sizeof(int))
self.c.labels = <int*>self.mem.alloc(len(doc), sizeof(int))
self.c.ner = <Transition*>self.mem.alloc(len(doc), sizeof(Transition))
self.tags = [None] * len(tokens)
self.heads = [None] * len(tokens)
self.labels = [''] * len(tokens)
self.ner = ['-'] * len(tokens)
self.tags = [None] * len(doc)
self.heads = [None] * len(doc)
self.labels = [''] * len(doc)
self.ner = ['-'] * len(doc)
self.cand_to_gold = align([t.orth_ for t in tokens], annot_tuples[1])
self.gold_to_cand = align(annot_tuples[1], [t.orth_ for t in tokens])
self.cand_to_gold = align([t.orth_ for t in doc], words)
self.gold_to_cand = align(words, [t.orth_ for t in doc])
annot_tuples = (range(len(words)), words, tags, heads, deps, entities)
self.orig_annot = list(zip(*annot_tuples))
words = [w.orth_ for w in tokens]
for i, gold_i in enumerate(self.cand_to_gold):
if words[i].isspace():
if doc[i].isspace():
self.tags[i] = 'SP'
self.heads[i] = None
self.labels[i] = None
self.ner[i] = 'O'
if gold_i is None:
elif gold_i is None:
pass
else:
self.tags[i] = annot_tuples[2][gold_i]
self.heads[i] = self.gold_to_cand[annot_tuples[3][gold_i]]
self.labels[i] = annot_tuples[4][gold_i]
self.ner[i] = annot_tuples[5][gold_i]
self.tags[i] = tags[gold_i]
self.heads[i] = self.gold_to_cand[heads[gold_i]]
self.labels[i] = deps[gold_i]
self.ner[i] = entities[gold_i]
cycle = nonproj.contains_cycle(self.heads)
if cycle != None:
raise Exception("Cycle found: %s" % cycle)
if make_projective:
proj_heads,_ = nonproj.PseudoProjectivity.projectivize(self.heads,self.labels)
proj_heads,_ = nonproj.PseudoProjectivity.projectivize(self.heads, self.labels)
self.heads = proj_heads
def __len__(self):