Question

我正在使用NLTK RegexpParser从标记的标记中提取noungroups和verbgroups。

如何查看结果树以仅查找NP或V组的块？

from nltk.chunk import RegexpParser

grammar = '''
NP: {<DT>?<JJ>*<NN>*}
V: {<V.*>}'''
chunker = RegexpParser(grammar)
token = [] ## Some tokens from my POS tagger
chunked = chunker.parse(tokens)
print chunked

#How do I walk the tree?
#for chunk in chunked:
#    if chunk.??? == 'NP':
#         print chunk

（S （NP运营商/ NN）为/ IN 组织 - / JJ 和/ CC 细胞培养/ JJ 为/ IN （NP / DT准备/ NN）中/ IN （NP植入物/ NNS）和/ CC （NP种植体/ NN）（V包含/ VBG）（NP / DT载波/ NN） ./.)

Answer 1

这应该有效：

for n in chunked:
    if isinstance(n, nltk.tree.Tree):               
        if n.label() == 'NP':
            do_something_with_subtree(n)
        else:
            do_something_with_leaf(n)

Answer 2

token

中的小错误

from nltk.chunk import RegexpParser
grammar = '''
NP: {<DT>?<JJ>*<NN>*}
V: {<V.*>}'''
chunker = RegexpParser(grammar)
token = [] ## Some tokens from my POS tagger
//chunked = chunker.parse(tokens) // token defined in the previous line but used tokens in chunker.parse(tokens)
chunked = chunker.parse(token) // Change in this line
print chunked

Answer 3

Savino的答案很棒，但同样值得注意的是，也可以通过索引访问子树，例如。

for n in range(len(chunked)):
    do_something_with_subtree(chunked[n])

Answer 4

def preprocess(sent):
sent = nltk.word_tokenize(sent)
sent = nltk.pos_tag(sent)
return sent



pattern = 'NP: {<JJ>*<NNP.*>*}'
cp =   nltk.RegexpParser(pattern)
exp = []
for line in lines:
    line = preprocess(line)
    cs = cp.parse(line)
    for n in cs:
        if isinstance(n, nltk.tree.Tree):
            if n.label() == 'NP':
                if len(n.leaves()) > 1:
                    req = ''
                    for leaf in n.leaves():
                        req += leaf[0]+' '
                    exp.append(req)
print(exp)

NLTK分块和走结果树

4 个答案: