42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
|
from typing import Iterator, Set, Tuple, Union
|
||
|
|
|
||
|
|
from ...symbols import NOUN, PRON, PROPN, VERB
|
||
|
|
from ...tokens import Doc, Span
|
||
|
|
|
||
|
|
# TODO: this can probably be pruned a bit
|
||
|
|
# fmt: off
|
||
|
|
labels = ["nsubj", "nmod", "ddoclike", "nsubjpass", "pcomp", "pdoclike", "doclike", "obl", "dative", "appos", "attr", "ROOT"]
|
||
|
|
# fmt: on
|
||
|
|
|
||
|
|
|
||
|
|
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
|
||
|
|
"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
|
||
|
|
doc = doclike.doc # Ensure works on both Doc and Span.
|
||
|
|
np_deps = [doc.vocab.strings.add(label) for label in labels]
|
||
|
|
doc.vocab.strings.add("conj")
|
||
|
|
np_label = doc.vocab.strings.add("NP")
|
||
|
|
seen: Set[int] = set()
|
||
|
|
for i, word in enumerate(doclike):
|
||
|
|
if word.pos not in (NOUN, PROPN, PRON):
|
||
|
|
continue
|
||
|
|
# Prevent nested chunks from being produced
|
||
|
|
if word.i in seen:
|
||
|
|
continue
|
||
|
|
if word.dep in np_deps:
|
||
|
|
unseen = [w.i for w in word.subtree if w.i not in seen]
|
||
|
|
if not unseen:
|
||
|
|
continue
|
||
|
|
# this takes care of particles etc.
|
||
|
|
seen.update(j.i for j in word.subtree)
|
||
|
|
# This avoids duplicating embedded clauses
|
||
|
|
seen.update(range(word.i + 1))
|
||
|
|
# if the head of this is a verb, mark that and rights seen
|
||
|
|
# Don't do the subtree as that can hide other phrases
|
||
|
|
if word.head.pos == VERB:
|
||
|
|
seen.add(word.head.i)
|
||
|
|
seen.update(w.i for w in word.head.rights)
|
||
|
|
yield unseen[0], word.i + 1, np_label
|
||
|
|
|
||
|
|
|
||
|
|
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
|