本文整理汇总了Python中nltk.corpus.util.LazyCorpusLoader.iob_sents方法的典型用法代码示例。如果您正苦于以下问题：Python LazyCorpusLoader.iob_sents方法的具体用法？Python LazyCorpusLoader.iob_sents怎么用？Python LazyCorpusLoader.iob_sents使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类nltk.corpus.util.LazyCorpusLoader的用法示例。
在下文中一共展示了LazyCorpusLoader.iob_sents方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: demo
# 需要导入模块: from nltk.corpus.util import LazyCorpusLoader [as 别名]
# 或者: from nltk.corpus.util.LazyCorpusLoader import iob_sents [as 别名]
def demo(**kwargs):
import nltk
from nltk_contrib.coref import NLTK_COREF_DATA
from nltk_contrib.coref.muc import muc6_documents, muc7_documents
from nltk_contrib.coref.muc import MUCCorpusReader
nltk.data.path.insert(0, NLTK_COREF_DATA)
muc6 = LazyCorpusLoader('muc6/', MUCCorpusReader, muc6_documents)
for sent in muc6.iob_sents()[:]:
for word in sent:
print word
print
print
for sent in muc6.mentions(depth=None):
for mention in sent:
print mention
if sent: print
print
muc7 = LazyCorpusLoader('muc7/', MUCCorpusReader, muc7_documents)
for sent in muc7.iob_sents()[:]:
for word in sent:
print word
print
print
for sent in muc7.mentions(depth=None):
for mention in sent:
print mention
if sent: print
print示例2: train_model
# 需要导入模块: from nltk.corpus.util import LazyCorpusLoader [as 别名]
# 或者: from nltk.corpus.util.LazyCorpusLoader import iob_sents [as 别名]
treebank_test_sequence = treebank_test.tagged_sents()
treebank_estimator = LidstoneProbDistFactory
model = train_model(HiddenMarkovModelTagger,
treebank_train_sequence,
treebank_test_sequence,
options.model_file,
options.num_train_sents,
options.num_test_sents,
estimator=treebank_estimator,
verbose=options.verbose)
elif options.train_chunker:
conll2k_train = LazyCorpusLoader(
'conll2000', ConllChunkCorpusReader,
['train.txt'], ('NP','VP','PP'))
conll2k_train_sequence = conll2k_train.iob_sents()
conll2k_test = LazyCorpusLoader(
'conll2000', ConllChunkCorpusReader,
['test.txt'], ('NP','VP','PP'))
conll2k_test_sequence = conll2k_test.iob_sents()
conll2k_estimator = LidstoneProbDistFactory
conll2k_transform = ClosedCategoryChunkTransform(TREEBANK_CLOSED_CATS)
model = train_model(HiddenMarkovModelChunkTagger,
conll2k_train_sequence,
conll2k_test_sequence,
options.model_file,
options.num_train_sents,
options.num_test_sents,
estimator=conll2k_estimator,
transform=conll2k_transform,
verbose=options.verbose)