How to lemmatize a list of sentences

Question

How can I lemmatize a list of sentences in Python?

from nltk.stem.wordnet import WordNetLemmatizer
a = [\'i like cars\', \'cats are the best\']
lmtzr = WordN         


        

Answer 1

You must lemmatize each word separately. Instead, you lemmatize sentences. Correct code fragment:

from nltk.stem.wordnet import WordNetLemmatizer
from nltk import word_tokenize
sents = ['i like cars', 'cats are the best']
lmtzr = WordNetLemmatizer()
lemmatized = [[lmtzr.lemmatize(word) for word in word_tokenize(s)]
              for s in sents]
print(lemmatized)
#[['i', 'like', 'car'], ['cat', 'are', 'the', 'best']]

You can also get better results if you first do POS tagging and then provide the POS information to the lemmatizer.

Answer 2

TL;DR:

pip3 install -U pywsd

Then:

>>> from pywsd.utils import lemmatize_sentence

>>> text = 'i like cars'
>>> lemmatize_sentence(text)
['i', 'like', 'car']
>>> lemmatize_sentence(text, keepWordPOS=True)
(['i', 'like', 'cars'], ['i', 'like', 'car'], ['n', 'v', 'n'])

>>> text = 'The cat likes cars'
>>> lemmatize_sentence(text, keepWordPOS=True)
(['The', 'cat', 'likes', 'cars'], ['the', 'cat', 'like', 'car'], [None, 'n', 'v', 'n'])

>>> text = 'The lazy brown fox jumps, and the cat likes cars.'
>>> lemmatize_sentence(text)
['the', 'lazy', 'brown', 'fox', 'jump', ',', 'and', 'the', 'cat', 'like', 'car', '.']

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Otherwise, take a look at how the function in pywsd:

• Tokenize the string
• Uses the POS tagger and maps to WordNet POS tagset
• Attempts to stem
• Finally calling the lemmatizer with the POS and/or stems

See https://github.com/alvations/pywsd/blob/master/pywsd/utils.py#L129