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# coding=utf-8 | |
# Copyright 2024 The Google Research Authors. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""Language processing utilities.""" | |
import spacy | |
def load_spacy_model(model='en_core_web_trf'): | |
nlp = spacy.load(model) | |
return nlp | |
def process_sentence(sentence, nlp): | |
"""Process a sentence.""" | |
doc = nlp(sentence) | |
sentence_for_spacy = [] | |
for _, token in enumerate(doc): | |
if token.text == ' ': | |
continue | |
sentence_for_spacy.append(token.text) | |
sentence_for_spacy = ' '.join(sentence_for_spacy) | |
noun_phrase, _, _ = extract_noun_phrase( | |
sentence_for_spacy, nlp, need_index=True | |
) | |
return noun_phrase | |
def extract_noun_phrase(text, nlp, need_index=False): | |
"""Extract noun phrase from text. nlp is a spacy model. | |
Args: | |
text: str, text to be processed. | |
nlp: spacy model. | |
need_index: bool, whether to return the index of the noun phrase. | |
Returns: | |
noun_phrase: str, noun phrase of the text. | |
""" | |
# text = text.lower() | |
doc = nlp(text) | |
chunks = {} | |
chunks_index = {} | |
for chunk in doc.noun_chunks: | |
for i in range(chunk.start, chunk.end): | |
chunks[i] = chunk | |
chunks_index[i] = (chunk.start, chunk.end) | |
for token in doc: | |
if token.head.i == token.i: | |
head = token.head | |
if head.i not in chunks: | |
children = list(head.children) | |
if children and children[0].i in chunks: | |
head = children[0] | |
else: | |
if need_index: | |
return text, [], text | |
else: | |
return text | |
head_noun = head.text | |
head_index = chunks_index[head.i] | |
head_index = [i for i in range(head_index[0], head_index[1])] | |
sentence_index = [i for i in range(len(doc))] | |
not_phrase_index = [] | |
for i in sentence_index: | |
# not_phrase_index.append(i) if i not in head_index else None | |
if i not in head_index: | |
not_phrase_index.append(i) | |
head = chunks[head.i] | |
if need_index: | |
return head.text, not_phrase_index, head_noun | |
else: | |
return head.text | |