Question

我是spacy的新手，我想使用它的lemmatizer函数，但我不知道如何使用它，就像我在单词串中一样，它会返回字符串的基本形式。< / p>

示例：

＆＃39;也就是说＆＃39; = GT; ＆＃39;字＆＃39;
＆＃39;做＆＃39; =＆GT; ＆＃39;做＆＃39;

谢谢。

Answer 1

以前的答案很复杂，无法编辑，所以这是一个更传统的答案。

# make sure your downloaded the english model with "python -m spacy download en"

import spacy
nlp = spacy.load('en')

doc = nlp(u"Apples and oranges are similar. Boots and hippos aren't.")

for token in doc:
    print(token, token.lemma, token.lemma_)

输出：

Apples 6617 apples
and 512 and
oranges 7024 orange
are 536 be
similar 1447 similar
. 453 .
Boots 4622 boot
and 512 and
hippos 98365 hippo
are 536 be
n't 538 not
. 453 .

来自official Lighting tour

Answer 2

代码：

import os
from spacy.en import English, LOCAL_DATA_DIR

data_dir = os.environ.get('SPACY_DATA', LOCAL_DATA_DIR)

nlp = English(data_dir=data_dir)

doc3 = nlp(u"this is spacy lemmatize testing. programming books are more better than others")

for token in doc3:
    print token, token.lemma, token.lemma_

输出

this 496 this
is 488 be
spacy 173779 spacy
lemmatize 1510965 lemmatize
testing 2900 testing
. 419 .
programming 3408 programming
books 1011 book
are 488 be
more 529 more
better 615 better
than 555 than
others 871 others

示例参考：here

Answer 3

如果你只想使用Lemmatizer。你可以通过以下方式做到这一点。

from spacy.lemmatizer import Lemmatizer
from spacy.lang.en import LEMMA_INDEX, LEMMA_EXC, LEMMA_RULES

lemmatizer = Lemmatizer(LEMMA_INDEX, LEMMA_EXC, LEMMA_RULES)
lemmas = lemmatizer(u'ducks', u'NOUN')
print(lemmas)

输出

['duck']

Answer 4

我使用Spacy 2.x版

import spacy
nlp = spacy.load('en_core_web_sm', disable=['parser', 'ner'])
doc = nlp('did displaying words')
print (" ".join([token.lemma_ for token in doc]))

和输出：

do display word

希望它会有所帮助：）

Answer 5

我用过：

import spacy

nlp = en_core_web_sm.load()
doc = nlp("did displaying words")
print(" ".join([token.lemma_ for token in doc]))
>>> do display word

但是它给了OSError: [E050] Can't find model 'en_core_web_sm'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.错误，我使用了：

pip3 install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz

摆脱错误。

如何使用spacy lemmatizer来获得基本形式的单词

5 个答案: