spaCy/spacy/pos_util.py
2014-10-22 10:17:57 +11:00

56 lines
1.7 KiB
Python

from __future__ import unicode_literals
from . import util
from . import tokens
from .en import EN
from .pos import Tagger
def realign_tagged(token_rules, tagged_line, sep='/'):
words, pos = zip(*[token.rsplit(sep, 1) for token in tagged_line.split()])
positions = util.detokenize(token_rules, words)
aligned = []
for group in positions:
w_group = [words[i] for i in group]
p_group = [pos[i] for i in group]
aligned.append('<SEP>'.join(w_group) + sep + '_'.join(p_group))
return ' '.join(aligned)
def read_tagged(detoken_rules, file_, sep='/'):
sentences = []
for line in file_:
line = realign_tagged(detoken_rules, line, sep=sep)
tokens, tags = _parse_line(line, sep)
assert len(tokens) == len(tags)
sentences.append((tokens, tags))
return sentences
def _parse_line(line, sep):
words = []
tags = []
for token_str in line.split():
word, pos = token_str.rsplit(sep, 1)
word = word.replace('<SEP>', '')
subtokens = EN.tokenize(word)
subtags = pos.split('_')
while len(subtags) < len(subtokens):
subtags.append('NULL')
assert len(subtags) == len(subtokens), [t.string for t in subtokens]
words.append(word)
tags.extend([Tagger.encode_pos(pos) for pos in subtags])
return EN.tokenize(' '.join(words)), tags
def get_tagdict(train_sents):
tagdict = {}
for tokens, tags in train_sents:
for i, tag in enumerate(tags):
if tag == 'NULL':
continue
word = tokens.string(i)
tagdict.setdefault(word, {}).setdefault(tag, 0)
tagdict[word][tag] += 1
return tagdict