本文整理汇总了Python中nltk.corpus.reader.ChunkedCorpusReader.chunked_sents方法的典型用法代码示例。如果您正苦于以下问题：Python ChunkedCorpusReader.chunked_sents方法的具体用法？Python ChunkedCorpusReader.chunked_sents怎么用？Python ChunkedCorpusReader.chunked_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.reader.ChunkedCorpusReader的用法示例。
在下文中一共展示了ChunkedCorpusReader.chunked_sents方法的3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: Tree
# 需要导入模块: from nltk.corpus.reader import ChunkedCorpusReader [as 别名]
# 或者: from nltk.corpus.reader.ChunkedCorpusReader import chunked_sents [as 别名]
########## CHUNKED CORPUS READER ###############
###Implementing CCR
from nltk.corpus.reader import ChunkedCorpusReader
root="C:\\Users\\Matrix\\AppData\\Roaming\\nltk_data\\corpora\\cookbook\\"
reader=ChunkedCorpusReader(root,r'.*\.chunk')
#Each chunk-represented in braces is considered as a word
print reader.chunked_words()
#Each sentence will be included in a Tree()
print reader.chunked_sents()
print reader.chunked_paras()
#Getting tagged tokens for each chunk (each chunk is a word but each word is not a chunk)
print reader.chunked_words()[0].leaves()
print reader.chunked_sents()[1].leaves()
#Cant apply leaves directly to a para - but we can access a sentence of a given para.
print reader.chunked_para()[0][0].leaves()
###Implementing CCCR
from nltk.corpus.reader import ConllChunkCorpusReader
root="C:\\Users\\Matrix\\AppData\\Roaming\\nltk_data\\corpora\\cookbook\\"
reader=ConllChunkCorpusReader(root,r'.*\.iob',('NP','VP'.'PP'))
print reader.chunked_words()
print reader.chunked_sents()
print reader.iob_words()
print reader.iob_sents()
示例2: chunked_sents
# 需要导入模块: from nltk.corpus.reader import ChunkedCorpusReader [as 别名]
# 或者: from nltk.corpus.reader.ChunkedCorpusReader import chunked_sents [as 别名]
def chunked_sents(self, fileids=None, categories=None):
return ChunkedCorpusReader.chunked_sents(
self, self._resolve(fileids, categories))示例3: createChunker
# 需要导入模块: from nltk.corpus.reader import ChunkedCorpusReader [as 别名]
# 或者: from nltk.corpus.reader.ChunkedCorpusReader import chunked_sents [as 别名]
def createChunker():
chunks = ChunkedCorpusReader('data/chunks/','text_search.pos')
tagger_classes = [UnigramTagger, BigramTagger]
train_chunks = chunks.chunked_sents()
chunker = TagChunker(train_chunks, tagger_classes)
return chunker