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* Update the CoNLL train script, to get working on other languages

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This commit is contained in:
Matthew Honnibal 2016-02-02 22:29:34 +01:00
parent 6c633f2edc
commit a676d66807
1 changed files with 15 additions and 7 deletions
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22
bin/parser/conll_train.py
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@ -5,7 +5,7 @@ from __future__ import unicode_literals
import os import os
from os import path from os import path
import shutil import shutil
import codecs import io
import random import random
import time import time
import gzip import gzip
@ -56,12 +56,20 @@ def _parse_line(line):
if len(pieces) == 4: if len(pieces) == 4:
word, pos, head_idx, label = pieces word, pos, head_idx, label = pieces
head_idx = int(head_idx) head_idx = int(head_idx)
elif len(pieces) == 15:
id_ = int(pieces[0].split('_')[-1])
word = pieces[1]
pos = pieces[4]
head_idx = int(pieces[8])-1
label = pieces[10]
else: else:
id_ = int(pieces[0]) id_ = int(pieces[0].split('_')[-1])
word = pieces[1] word = pieces[1]
pos = pieces[4] pos = pieces[4]
head_idx = int(pieces[6])-1 head_idx = int(pieces[6])-1
label = pieces[7] label = pieces[7]
if head_idx == 0:
label = 'ROOT'
return word, pos, head_idx, label return word, pos, head_idx, label
@ -69,8 +77,8 @@ def score_model(scorer, nlp, raw_text, annot_tuples, verbose=False):
tokens = nlp.tokenizer.tokens_from_list(annot_tuples[1]) tokens = nlp.tokenizer.tokens_from_list(annot_tuples[1])
nlp.tagger(tokens) nlp.tagger(tokens)
nlp.parser(tokens) nlp.parser(tokens)
gold = GoldParse(tokens, annot_tuples) gold = GoldParse(tokens, annot_tuples, make_projective=False)
scorer.score(tokens, gold, verbose=verbose) scorer.score(tokens, gold, verbose=verbose, punct_labels=('--', 'p', 'punct'))
def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic', seed=0, def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic', seed=0,
@ -122,11 +130,11 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic', seed=0
def main(train_loc, dev_loc, model_dir): def main(train_loc, dev_loc, model_dir):
with codecs.open(train_loc, 'r', 'utf8') as file_: with io.open(train_loc, 'r', encoding='utf8') as file_:
train_sents = read_conll(file_) train_sents = read_conll(file_)
train(English, train_sents, model_dir) #train(English, train_sents, model_dir)
nlp = English(data_dir=model_dir) nlp = English(data_dir=model_dir)
dev_sents = read_conll(open(dev_loc)) dev_sents = read_conll(io.open(dev_loc, 'r', encoding='utf8'))
scorer = Scorer() scorer = Scorer()
for _, sents in dev_sents: for _, sents in dev_sents:
for annot_tuples, _ in sents: for annot_tuples, _ in sents: