Source code for

# ******************************************************************************
# Copyright 2017-2018 Intel Corporation
# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
import logging
import os
from typing import List, Set

from nlp_architect.common.cdc.mention_data import MentionData
from import RelationExtraction
from import RelationType
from import load_json_file

logger = logging.getLogger(__name__)

[docs]class WithinDocCoref(RelationExtraction): def __init__(self, wd_file: str): """ Extract Relation between two mentions according to Within document co-reference Args: wd_file (required): str Location of within doc co-reference mentions file """"Loading Within doc resource") if wd_file is not None and os.path.isfile(wd_file): wd_mentions_json = load_json_file(wd_file) self.within_doc_coref_chain = self.arrange_resource(wd_mentions_json) else: raise FileNotFoundError("Within-doc resource file not found or not in path") super(WithinDocCoref, self).__init__()
[docs] @staticmethod def arrange_resource(wd_mentions_json): document_tokens_dict = dict() for mention_json in wd_mentions_json: mention_data = MentionData.read_json_mention_data_line(mention_json) mention_tokens = mention_data.tokens_number for i in range(0, len(mention_tokens)): doc_id = mention_data.doc_id sent_id = mention_data.sent_id token_map_key = MentionData.static_gen_token_unique_id( doc_id, sent_id, mention_tokens[i] ) document_tokens_dict[token_map_key] = mention_data.coref_chain return document_tokens_dict
[docs] def extract_all_relations( self, mention_x: MentionData, mention_y: MentionData ) -> Set[RelationType]: ret_ = set() ret_.add(self.extract_sub_relations(mention_x, mention_y, RelationType.WITHIN_DOC_COREF)) return ret_
[docs] def extract_sub_relations( self, mention_x: MentionData, mention_y: MentionData, relation: RelationType ) -> RelationType: """ Check if input mentions has the given relation between them Args: mention_x: MentionDataLight mention_y: MentionDataLight relation: RelationType Returns: RelationType: relation in case mentions has given relation or RelationType.NO_RELATION_FOUND otherwise """ if relation is not RelationType.WITHIN_DOC_COREF: return RelationType.NO_RELATION_FOUND if mention_x.doc_id == mention_y.doc_id: ment_x_coref_chain = self.extract_within_coref(mention_x) ment_y_coref_chain = self.extract_within_coref(mention_y) if not ment_x_coref_chain or not ment_y_coref_chain: return RelationType.NO_RELATION_FOUND if "-" in ment_x_coref_chain or "-" in ment_y_coref_chain: return RelationType.NO_RELATION_FOUND if set(ment_x_coref_chain) == set(ment_y_coref_chain): return RelationType.WITHIN_DOC_COREF return RelationType.NO_RELATION_FOUND
[docs] def extract_within_coref(self, mention: MentionData) -> List[str]: tokens = mention.tokens_number within_coref_token = [] for token_id in tokens: token_x_id = MentionData.static_gen_token_unique_id( str(mention.doc_id), str(mention.sent_id), str(token_id) ) if token_x_id in self.within_doc_coref_chain: token_coref_chain = self.within_doc_coref_chain[token_x_id] if token_coref_chain: within_coref_token.append(token_coref_chain) else: within_coref_token.append("-") break return within_coref_token
[docs] def get_within_doc_coref_chain(self): return self.within_doc_coref_chain
[docs] @staticmethod def create_ment_id(mention_x: MentionData, mention_y: MentionData) -> str: return "_".join([mention_x.get_mention_id(), mention_y.get_mention_id()])
[docs] @staticmethod def get_supported_relations() -> List[RelationType]: """ Return all supported relations by this class Returns: List[RelationType] """ return [RelationType.WITHIN_DOC_COREF]