ai-content-maker/.venv/Lib/site-packages/spacy/lang/de/syntax_iterators.py

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2024-05-03 04:18:51 +03:00
from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
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."""
# this iterator extracts spans headed by NOUNs starting from the left-most
# syntactic dependent until the NOUN itself for close apposition and
# measurement construction, the span is sometimes extended to the right of
# the NOUN. Example: "eine Tasse Tee" (a cup (of) tea) returns "eine Tasse Tee"
# and not just "eine Tasse", same for "das Thema Familie".
# fmt: off
labels = ["sb", "oa", "da", "nk", "mo", "ag", "ROOT", "root", "cj", "pd", "og", "app"]
# fmt: on
doc = doclike.doc # Ensure works on both Doc and Span.
if not doc.has_annotation("DEP"):
raise ValueError(Errors.E029)
np_label = doc.vocab.strings.add("NP")
np_deps = set(doc.vocab.strings.add(label) for label in labels)
close_app = doc.vocab.strings.add("nk")
rbracket = 0
prev_end = -1
for i, word in enumerate(doclike):
if i < rbracket:
continue
# Prevent nested chunks from being produced
if word.left_edge.i <= prev_end:
continue
if word.pos in (NOUN, PROPN, PRON) and word.dep in np_deps:
rbracket = word.i + 1
# try to extend the span to the right
# to capture close apposition/measurement constructions
for rdep in doc[word.i].rights:
if rdep.pos in (NOUN, PROPN) and rdep.dep == close_app:
rbracket = rdep.i + 1
prev_end = rbracket - 1
yield word.left_edge.i, rbracket, np_label
SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}