Question

我正在尝试使用nltk在一些LaTeX文件中查找名词短语（NP）和动词短语（VP）。我的LaTeX文件包含大量数学。因为我是nltk的新手，所以我开始尝试从终端获得我需要的东西。所以我举了这句话：

让尺寸分别用 $s(n)$ 和 $t(n)$ 表示。

我试过的代码：

>>> from nltk import sent_tokenize, word_tokenize, pos_tag

>>> text = "Let the sizes be denoted by $s(n)$ and $t(n)$ respectively."

>>> sents = sent_tokenize(text)

>>> tokens = word_tokenize(text)

>>> tagged_tokens = pos_tag(tokens)

所有这些都很好。但是当我尝试这些时：

>>> from nltk.chunk import *

>>> from nltk.chunk.util import *

>>> from nltk.chunk.regexp import *

>>> from nltk import Tree

>>> gold_chunked_text = tagstr2tree(tagged_tokens)

我收到了这个错误：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/nltk/chunk/util.py", line 331, in tagstr2tree
    for match in WORD_OR_BRACKET.finditer(s):
TypeError: expected string or buffer

知道问题是什么？

Answer 1

tagstr2tree()函数需要一个字符串输入，但是您已经为pos_tag()输出了一个元组列表：

>>> from nltk import word_tokenize, pos_tag
>>> text = "Let the sizes be denoted by $s(n)$ and $t(n)$ respectively."
>>> tagged_text = pos_tag(word_tokenize(text))
>>> tagged_text
[('Let', 'NNP'), ('the', 'DT'), ('sizes', 'NNS'), ('be', 'VB'), ('denoted', 'VBN'), ('by', 'IN'), ('$', '$'), ('s', 'NNS'), ('(', 'CD'), ('n', 'NN'), (')', ':'), ('$', '$'), ('and', 'CC'), ('$', '$'), ('t', 'NN'), ('(', ':'), ('n', 'NN'), (')', ':'), ('$', '$'), ('respectively', 'RB'), ('.', '.')]

现在你看到pos_tag可能没有给你你需要的东西，所以这可能是一种更好的标记方式：

>>> tagged_text = pos_tag(text.split())
>>> tagged_text
[('Let', 'NNP'), ('the', 'DT'), ('sizes', 'NNS'), ('be', 'VB'), ('denoted', 'VBN'), ('by', 'IN'), ('$s(n)$', 'NNP'), ('and', 'CC'), ('$t(n)$', 'NNP'), ('respectively.', 'NNP')]

回到tagstr2tree，预期的输入如下所示：

'Let/NNP the/DT sizes/NNS be/VB denoted/VBN by/IN $s(n)$/NNP and/CC $t(n)$/NNP respectively./NNP'

要做到这一点：

>>> " ".join(["{}/{}".format(word,pos) for word, pos in tagged_text])

这是完整的脚本：

>>> from nltk.chunk.util import tagstr2tree
>>> from nltk import word_tokenize, pos_tag
>>> text = "Let the sizes be denoted by $s(n)$ and $t(n)$ respectively."
>>> tagged_text = pos_tag(text.split())
>>> tagged_text_string = " ".join(["{}/{}".format(word,pos) for word, pos in tagged_text])
>>> tagstr2tree(tagged_text_string)
Tree('S', [('Let', 'NNP'), ('the', 'DT'), ('sizes', 'NNS'), ('be', 'VB'), ('denoted', 'VBN'), ('by', 'IN'), ('$s(n)$', 'NNP'), ('and', 'CC'), ('$t(n)$', 'NNP'), ('respectively.', 'NNP')])

使用nltk的块NP和VP

1 个答案: