spaCy/spacy/lang/el/syntax_iterators.py
Adriane Boyd 7e4cd7575c
Refactor Docs.is_ flags (#6044)
* 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>
2020-09-17 00:14:01 +02:00

54 lines
2.2 KiB
Python

from typing import Union, Iterator
from ...symbols import NOUN, PROPN, PRON
from ...errors import Errors
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Span]:
"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
# It follows the logic of the noun chunks finder of English language,
# adjusted to some Greek language special characteristics.
# obj tag corrects some DEP tagger mistakes.
# Further improvement of the models will eliminate the need for this tag.
labels = ["nsubj", "obj", "iobj", "appos", "ROOT", "obl"]
doc = doclike.doc # Ensure works on both Doc and Span.
if not doc.has_annotation("DEP"):
raise ValueError(Errors.E029)
np_deps = [doc.vocab.strings.add(label) for label in labels]
conj = doc.vocab.strings.add("conj")
nmod = doc.vocab.strings.add("nmod")
np_label = doc.vocab.strings.add("NP")
prev_end = -1
for i, word in enumerate(doclike):
if word.pos not in (NOUN, PROPN, PRON):
continue
# Prevent nested chunks from being produced
if word.left_edge.i <= prev_end:
continue
if word.dep in np_deps:
flag = False
if word.pos == NOUN:
# check for patterns such as γραμμή παραγωγής
for potential_nmod in word.rights:
if potential_nmod.dep == nmod:
prev_end = potential_nmod.i
yield word.left_edge.i, potential_nmod.i + 1, np_label
flag = True
break
if flag is False:
prev_end = word.i
yield word.left_edge.i, word.i + 1, np_label
elif word.dep == conj:
# covers the case: έχει όμορφα και έξυπνα παιδιά
head = word.head
while head.dep == conj and head.head.i < head.i:
head = head.head
# If the head is an NP, and we're coordinated to it, we're an NP
if head.dep in np_deps:
prev_end = word.i
yield word.left_edge.i, word.i + 1, np_label
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}