How can I break a document (e.g., paragraph, book, etc) into sentences.
For example, "The dog ran. The cat jumped"
into ["The dog ran", "The cat jumped"]
with spacy?
The up-to-date answer is this:
from __future__ import unicode_literals, print_function
from spacy.lang.en import English # updated
raw_text = 'Hello, world. Here are two sentences.'
nlp = English()
nlp.add_pipe(nlp.create_pipe('sentencizer')) # updated
doc = nlp(raw_text)
sentences = [sent.string.strip() for sent in doc.sents]
Answer
import spacy
nlp = spacy.load('en_core_web_sm')
text = 'My first birthday was great. My 2. was even better.'
sentences = [i for i in nlp(text).sents]
Additional info
This assumes that you have already installed the model "en_core_web_sm" on your system. If not, you can easily install it by running the following command in your terminal:
$ python -m spacy download en_core_web_sm
(See here for an overview of all available models.)
Depending on your data this can lead to better results than just using spacy.lang.en.English
. One (very simple) comparison example:
import spacy
from spacy.lang.en import English
nlp_simple = English()
nlp_simple.add_pipe(nlp_simple.create_pipe('sentencizer'))
nlp_better = spacy.load('en_core_web_sm')
text = 'My first birthday was great. My 2. was even better.'
for nlp in [nlp_simple, nlp_better]:
for i in nlp(text).sents:
print(i)
print('-' * 20)
Outputs:
>>> My first birthday was great.
>>> My 2.
>>> was even better.
>>> --------------------
>>> My first birthday was great.
>>> My 2. was even better.
>>> --------------------
From spacy's github support page
from __future__ import unicode_literals, print_function
from spacy.en import English
raw_text = 'Hello, world. Here are two sentences.'
nlp = English()
doc = nlp(raw_text)
sentences = [sent.string.strip() for sent in doc.sents]
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