Question

我将Ted数据集成绩单搞得一团糟。我注意到有些奇怪的东西：并非所有的词都被词状化。说，

selected -> select

哪个是对的。

但是，involved !-> involve和horsing !-> horse除非我明确输入'v'（Verb）属性。

在python终端上，我得到了正确的输出但不在我的code中：

>>> from nltk.stem import WordNetLemmatizer
>>> from nltk.corpus import wordnet
>>> lem = WordNetLemmatizer()
>>> lem.lemmatize('involved','v')
u'involve'
>>> lem.lemmatize('horsing','v')
u'horse'

代码的相关部分是：

for l in LDA_Row[0].split('+'):
    w=str(l.split('*')[1])
    word=lmtzr.lemmatize(w)
    wordv=lmtzr.lemmatize(w,'v')
    print wordv, word
    # if word is not wordv:
    #   print word, wordv

整个代码为here。

有什么问题？

Answer 1

lemmatizer要求正确的POS标记准确无误，如果使用WordNetLemmatizer.lemmatize()的默认设置，默认标记为名词，请参阅https://github.com/nltk/nltk/blob/develop/nltk/stem/wordnet.py#L39

要解决此问题，请始终在引理之前对数据进行POS标记，例如

>>> from nltk.stem import WordNetLemmatizer
>>> from nltk import pos_tag, word_tokenize
>>> wnl = WordNetLemmatizer()
>>> sent = 'This is a foo bar sentence'
>>> pos_tag(word_tokenize(sent))
[('This', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('foo', 'NN'), ('bar', 'NN'), ('sentence', 'NN')]
>>> for word, tag in pos_tag(word_tokenize(sent)):
...     wntag = tag[0].lower()
...     wntag = wntag if wntag in ['a', 'r', 'n', 'v'] else None
...     if not wntag:
...             lemma = word
...     else:
...             lemma = wnl.lemmatize(word, wntag)
...     print lemma
... 
This
be
a
foo
bar
sentence

请注意＆＃39;是 - ＆gt; be＆＃39;，即

>>> wnl.lemmatize('is')
'is'
>>> wnl.lemmatize('is', 'v')
u'be'

用你的例子中的文字来回答这个问题：

>>> sent = 'These sentences involves some horsing around'
>>> for word, tag in pos_tag(word_tokenize(sent)):
...     wntag = tag[0].lower()
...     wntag = wntag if wntag in ['a', 'r', 'n', 'v'] else None
...     lemma = wnl.lemmatize(word, wntag) if wntag else word
...     print lemma
... 
These
sentence
involve
some
horse
around

请注意，WordNetLemmatizer存在一些怪癖：

此外，NLTK的默认POS标签正在进行一些重大改变，以提高准确性：

对于一个开箱即用/现成的解码器解决方案，你可以看一下https://github.com/alvations/pywsd以及我是如何做出一些尝试的例子来捕捉到不在WordNet中，请参阅https://github.com/alvations/pywsd/blob/master/pywsd/utils.py#L66

除非POS是显式的，否则WordNetLemmatizer不会返回正确的引理 - Python NLTK

1 个答案: