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A small bug I came across in spaCy's lemmatization when using 's in sentences.
Example 1: In [6]: [token.lemma_ for token in en_nlp("Jane's got a new car")] Out[6]: ['jane', "'", 'get', 'a', 'new', 'car']
Here I'd expect it to extract either "Jane" or "Jane has".
In [7]: [token.lemma_ for token in en_nlp("Jane's my friend")] Out[7]: ['jane', "'s", 'my', 'friend']
Here perhaps "Jane is".
In [8]: [token.lemma_ for token in en_nlp("Jane thinks that's a nice car")] Out[8]: ['jane', 'think', 'that', "'", 'a', 'nice', 'car']
And here just an example of a non-entity token.
Thanks
The text was updated successfully, but these errors were encountered:
Hi,
A small bug I came across in spaCy's lemmatization when using
's
in sentences.Example 1:
In [6]: [token.lemma_ for token in en_nlp("Jane's got a new car")] Out[6]: ['jane', "'", 'get', 'a', 'new', 'car']
Here I'd expect it to extract either "Jane" or "Jane has".
In [7]: [token.lemma_ for token in en_nlp("Jane's my friend")] Out[7]: ['jane', "'s", 'my', 'friend']
Here perhaps "Jane is".
In [8]: [token.lemma_ for token in en_nlp("Jane thinks that's a nice car")] Out[8]: ['jane', 'think', 'that', "'", 'a', 'nice', 'car']
And here just an example of a non-entity token.
Thanks
The text was updated successfully, but these errors were encountered: