mirror of https://github.com/explosion/spaCy.git
Add doc.is_sentenced attribute, re #1959
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@ -186,6 +186,20 @@ cdef class Doc:
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def _(self):
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return Underscore(Underscore.doc_extensions, self)
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@property
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def is_sentenced(self):
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# Check if the document has sentence boundaries,
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# i.e at least one tok has the sent_start in (-1, 1)
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if 'sents' in self.user_hooks:
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return True
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if self.is_parsed:
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return True
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for i in range(self.length):
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if self.c[i].sent_start == -1 or self.c[i].sent_start == 1:
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return True
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else:
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return False
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def __getitem__(self, object i):
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"""Get a `Token` or `Span` object.
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@ -515,22 +529,16 @@ cdef class Doc:
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>>> assert [s.root.text for s in doc.sents] == ["is", "'s"]
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"""
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def __get__(self):
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if 'sents' in self.user_hooks:
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yield from self.user_hooks['sents'](self)
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return
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cdef int i
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if not self.is_parsed:
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for i in range(1, self.length):
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if self.c[i].sent_start != 0:
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break
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else:
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if not self.is_sentenced:
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raise ValueError(
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"Sentence boundaries unset. You can add the 'sentencizer' "
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"component to the pipeline with: "
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"nlp.add_pipe(nlp.create_pipe('sentencizer')) "
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"Alternatively, add the dependency parser, or set "
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"sentence boundaries by setting doc[i].sent_start")
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if 'sents' in self.user_hooks:
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yield from self.user_hooks['sents'](self)
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else:
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start = 0
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for i in range(1, self.length):
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if self.c[i].sent_start == 1:
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@ -300,17 +300,7 @@ cdef class Span:
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if n >= self.doc.length:
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raise RuntimeError
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return self.doc[root.l_edge:root.r_edge + 1]
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else:
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# Check if the document has sentence boundaries,
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# i.e at least one tok has the sent_start == 1
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for i in range(self.doc.length):
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if self.doc.c[i].sent_start == 1:
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break
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else:
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raise ValueError(
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"Access to sentence requires either the dependency parse "
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"or sentence boundaries to be set by setting " +
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"doc[i].is_sent_start = True")
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elif self.doc.is_sentenced:
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# find start of the sentence
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start = self.start
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while self.doc.c[start].sent_start != 1 and start > 0:
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@ -323,7 +313,11 @@ cdef class Span:
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break
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#
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return self.doc[start:end]
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else:
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raise ValueError(
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"Access to sentence requires either the dependency parse "
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"or sentence boundaries to be set by setting " +
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"doc[i].is_sent_start = True")
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property has_vector:
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"""RETURNS (bool): Whether a word vector is associated with the object.
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