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Add is_sent_end token property (#5375)
Reconstruction of the original PR #4697 by @MiniLau. Removes unused `SENT_END` symbol and `IS_SENT_END` from `Matcher` schema because the Matcher is only going to be able to support `IS_SENT_START`.
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# spaCy contributor agreement
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This spaCy Contributor Agreement (**"SCA"**) is based on the
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[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
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The SCA applies to any contribution that you make to any product or project
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If you agree to be bound by these terms, fill in the information requested
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should be your GitHub username, with the extension `.md`. For example, the user
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Read this agreement carefully before signing. These terms and conditions
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## Contributor Agreement
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1. The term "contribution" or "contributed materials" means any source code,
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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | Desausoi Laurent |
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| Company name (if applicable) | / |
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| Title or role (if applicable) | / |
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| Date | 22 November 2019 |
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| GitHub username | MiniLau |
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| Website (optional) | / |
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@ -94,3 +94,4 @@ cdef enum attr_id_t:
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ENT_ID = symbols.ENT_ID
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IDX
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SENT_END
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@ -88,6 +88,7 @@ IDS = {
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"ENT_KB_ID": ENT_KB_ID,
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"HEAD": HEAD,
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"SENT_START": SENT_START,
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"SENT_END": SENT_END,
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"SPACY": SPACY,
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"PROB": PROB,
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"LANG": LANG,
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@ -559,6 +559,8 @@ class Errors(object):
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"({curr_dim}).")
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E194 = ("Unable to aligned mismatched text '{text}' and words '{words}'.")
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E195 = ("Matcher can be called on {good} only, got {got}.")
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E196 = ("Refusing to write to token.is_sent_end. Sentence boundaries can "
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"only be fixed with token.is_sent_start.")
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@add_codes
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@ -84,7 +84,7 @@ cdef struct TokenC:
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cdef struct MorphAnalysisC:
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univ_pos_t pos
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int length
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attr_t abbr
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attr_t adp_type
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attr_t adv_type
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@ -464,4 +464,4 @@ cdef enum symbol_t:
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ENT_KB_ID
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ENT_ID
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IDX
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IDX
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@ -181,6 +181,14 @@ def test_is_sent_start(en_tokenizer):
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doc.is_parsed = True
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assert len(list(doc.sents)) == 2
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def test_is_sent_end(en_tokenizer):
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doc = en_tokenizer("This is a sentence. This is another.")
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assert doc[4].is_sent_end is None
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doc[5].is_sent_start = True
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assert doc[4].is_sent_end is True
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doc.is_parsed = True
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assert len(list(doc.sents)) == 2
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def test_set_pos():
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doc = Doc(Vocab(), words=["hello", "world"])
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@ -205,6 +213,12 @@ def test_token0_has_sent_start_true():
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assert doc[1].is_sent_start is None
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assert not doc.is_sentenced
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def test_tokenlast_has_sent_end_true():
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doc = Doc(Vocab(), words=["hello", "world"])
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assert doc[0].is_sent_end is None
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assert doc[1].is_sent_end is True
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assert not doc.is_sentenced
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def test_token_api_conjuncts_chain(en_vocab):
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words = "The boy and the girl and the man went .".split()
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@ -14,7 +14,9 @@ def test_sentencizer(en_vocab):
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doc = sentencizer(doc)
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assert doc.is_sentenced
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sent_starts = [t.is_sent_start for t in doc]
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sent_ends = [t.is_sent_end for t in doc]
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assert sent_starts == [True, False, True, False, False, False, False]
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assert sent_ends == [False, True, False, False, False, False, True]
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assert len(list(doc.sents)) == 2
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@ -46,13 +48,14 @@ def test_sentencizer_empty_docs():
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@pytest.mark.parametrize(
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"words,sent_starts,n_sents",
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"words,sent_starts,sent_ends,n_sents",
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[
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# The expected result here is that the duplicate punctuation gets merged
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# onto the same sentence and no one-token sentence is created for them.
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(
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["Hello", "!", ".", "Test", ".", ".", "ok"],
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[True, False, False, True, False, False, True],
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[False, False, True, False, False, True, True],
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3,
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),
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# We also want to make sure ¡ and ¿ aren't treated as sentence end
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@ -60,32 +63,36 @@ def test_sentencizer_empty_docs():
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(
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["¡", "Buen", "día", "!", "Hola", ",", "¿", "qué", "tal", "?"],
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[True, False, False, False, True, False, False, False, False, False],
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[False, False, False, True, False, False, False, False, False, True],
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2,
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),
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# The Token.is_punct check ensures that quotes are handled as well
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(
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['"', "Nice", "!", '"', "I", "am", "happy", "."],
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[True, False, False, False, True, False, False, False],
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[False, False, False, True, False, False, False, True],
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2,
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),
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],
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)
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def test_sentencizer_complex(en_vocab, words, sent_starts, n_sents):
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def test_sentencizer_complex(en_vocab, words, sent_starts, sent_ends, n_sents):
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doc = Doc(en_vocab, words=words)
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sentencizer = Sentencizer()
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doc = sentencizer(doc)
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assert doc.is_sentenced
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assert [t.is_sent_start for t in doc] == sent_starts
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assert [t.is_sent_end for t in doc] == sent_ends
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assert len(list(doc.sents)) == n_sents
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@pytest.mark.parametrize(
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"punct_chars,words,sent_starts,n_sents",
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"punct_chars,words,sent_starts,sent_ends,n_sents",
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[
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(
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["~", "?"],
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["Hello", "world", "~", "A", ".", "B", "."],
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[True, False, False, True, False, False, False],
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[False, False, True, False, False, False, True],
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2,
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),
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# Even thought it's not common, the punct_chars should be able to
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@ -94,16 +101,18 @@ def test_sentencizer_complex(en_vocab, words, sent_starts, n_sents):
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[".", "ö"],
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["Hello", ".", "Test", "ö", "Ok", "."],
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[True, False, True, False, True, False],
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[False, True, False, True, False, True],
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3,
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),
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],
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)
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def test_sentencizer_custom_punct(en_vocab, punct_chars, words, sent_starts, n_sents):
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def test_sentencizer_custom_punct(en_vocab, punct_chars, words, sent_starts, sent_ends, n_sents):
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doc = Doc(en_vocab, words=words)
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sentencizer = Sentencizer(punct_chars=punct_chars)
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doc = sentencizer(doc)
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assert doc.is_sentenced
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assert [t.is_sent_start for t in doc] == sent_starts
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assert [t.is_sent_end for t in doc] == sent_ends
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assert len(list(doc.sents)) == n_sents
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@ -493,6 +493,28 @@ cdef class Token:
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else:
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raise ValueError(Errors.E044.format(value=value))
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property is_sent_end:
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"""A boolean value indicating whether the token ends a sentence.
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`None` if unknown. Defaults to `True` for the last token in the `Doc`.
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RETURNS (bool / None): Whether the token ends a sentence.
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None if unknown.
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DOCS: https://spacy.io/api/token#is_sent_end
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"""
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def __get__(self):
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if self.i + 1 == len(self.doc):
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return True
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elif self.doc[self.i+1].is_sent_start == None:
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return None
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elif self.doc[self.i+1].is_sent_start == True:
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return True
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else:
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return False
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def __set__(self, value):
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raise ValueError(Errors.E196)
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@property
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def lefts(self):
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"""The leftward immediate children of the word, in the syntactic
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@ -352,7 +352,22 @@ property to `0` for the first word of the document.
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+ assert doc[4].is_sent_start == True
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```
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</Infobox>
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## Token.is_sent_end {#is_sent_end tag="property" new="2"}
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A boolean value indicating whether the token ends a sentence. `None` if
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unknown. Defaults to `True` for the last token in the `Doc`.
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> #### Example
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>
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> ```python
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> doc = nlp("Give it back! He pleaded.")
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> assert doc[3].is_sent_end
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> assert not doc[4].is_sent_end
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> ```
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| Name | Type | Description |
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| ----------- | ---- | ------------------------------------ |
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| **RETURNS** | bool | Whether the token ends a sentence. |
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## Token.has_vector {#has_vector tag="property" model="vectors"}
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