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7e4cd7575c
* Refactor Docs.is_ flags
* Add derived `Doc.has_annotation` method
* `Doc.has_annotation(attr)` returns `True` for partial annotation
* `Doc.has_annotation(attr, require_complete=True)` returns `True` for
complete annotation
* Add deprecation warnings to `is_tagged`, `is_parsed`, `is_sentenced`
and `is_nered`
* Add `Doc._get_array_attrs()`, which returns a full list of `Doc` attrs
for use with `Doc.to_array`, `Doc.to_bytes` and `Doc.from_docs`. The
list is the `DocBin` attributes list plus `SPACY` and `LENGTH`.
Notes on `Doc.has_annotation`:
* `HEAD` is converted to `DEP` because heads don't have an unset state
* Accept `IS_SENT_START` as a synonym of `SENT_START`
Additional changes:
* Add `NORM`, `ENT_ID` and `SENT_START` to default attributes for
`DocBin`
* In `Doc.from_array()` the presence of `DEP` causes `HEAD` to override
`SENT_START`
* In `Doc.from_array()` using `attrs` other than
`Doc._get_array_attrs()` (i.e., a user's custom list rather than our
default internal list) with both `HEAD` and `SENT_START` shows a warning
that `HEAD` will override `SENT_START`
* `set_children_from_heads` does not require dependency labels to set
sentence boundaries and sets `sent_start` for all non-sentence starts to
`-1`
* Fix call to set_children_form_heads
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
54 lines
2.2 KiB
Python
54 lines
2.2 KiB
Python
from typing import Union, Iterator
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from ...symbols import NOUN, PROPN, PRON
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from ...errors import Errors
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from ...tokens import Doc, Span
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def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Span]:
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"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
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# It follows the logic of the noun chunks finder of English language,
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# adjusted to some Greek language special characteristics.
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# obj tag corrects some DEP tagger mistakes.
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# Further improvement of the models will eliminate the need for this tag.
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labels = ["nsubj", "obj", "iobj", "appos", "ROOT", "obl"]
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doc = doclike.doc # Ensure works on both Doc and Span.
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if not doc.has_annotation("DEP"):
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raise ValueError(Errors.E029)
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np_deps = [doc.vocab.strings.add(label) for label in labels]
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conj = doc.vocab.strings.add("conj")
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nmod = doc.vocab.strings.add("nmod")
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np_label = doc.vocab.strings.add("NP")
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prev_end = -1
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for i, word in enumerate(doclike):
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if word.pos not in (NOUN, PROPN, PRON):
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continue
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# Prevent nested chunks from being produced
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if word.left_edge.i <= prev_end:
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continue
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if word.dep in np_deps:
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flag = False
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if word.pos == NOUN:
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# check for patterns such as γραμμή παραγωγής
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for potential_nmod in word.rights:
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if potential_nmod.dep == nmod:
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prev_end = potential_nmod.i
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yield word.left_edge.i, potential_nmod.i + 1, np_label
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flag = True
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break
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if flag is False:
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prev_end = word.i
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yield word.left_edge.i, word.i + 1, np_label
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elif word.dep == conj:
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# covers the case: έχει όμορφα και έξυπνα παιδιά
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head = word.head
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while head.dep == conj and head.head.i < head.i:
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head = head.head
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# If the head is an NP, and we're coordinated to it, we're an NP
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if head.dep in np_deps:
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prev_end = word.i
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yield word.left_edge.i, word.i + 1, np_label
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SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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