# ******************************************************************************
# 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
#
# 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,
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import logging
from typing import List
from nlp_architect.common.cdc.cluster import Clusters
from nlp_architect.common.cdc.topics import Topics
from nlp_architect.models.cross_doc_coref.system.sieves.run_sieve_system import get_run_system
from nlp_architect.models.cross_doc_coref.system.sieves_container_init import (
SievesContainerInitialization,
)
logger = logging.getLogger(__name__)
[docs]def run_event_coref(topics: Topics, resources: SievesContainerInitialization) -> List[Clusters]:
"""
Running Cross Document Coref on event mentions
Args:
topics : The Topics (with mentions) to evaluate
resources: resources for running the evaluation
Returns:
Clusters: List of clusters and mentions with predicted cross doc coref within each topic
"""
return _run_coref(topics, resources, "event")
[docs]def run_entity_coref(topics: Topics, resources: SievesContainerInitialization) -> List[Clusters]:
"""
Running Cross Document Coref on Entity mentions
Args:
topics : The Topics (with mentions) to evaluate
resources: (SievesContainerInitialization) resources for running the evaluation
Returns:
Clusters: List of topics and mentions with predicted cross doc coref within each topic
"""
return _run_coref(topics, resources, "entity")
def _run_coref(
topics: Topics, resources: SievesContainerInitialization, eval_type: str
) -> List[Clusters]:
"""
Running Cross Document Coref on Entity mentions
Args:
resources: (SievesContainerInitialization) resources for running the evaluation
topics : The Topics (with mentions) to evaluate
Returns:
Clusters: List of topics and mentions with predicted cross doc coref within each topic
"""
clusters_list = list()
for topic in topics.topics_list:
sieves_list = get_run_system(topic, resources, eval_type)
clusters = sieves_list.run_deterministic()
clusters.set_coref_chain_to_mentions()
clusters_list.append(clusters)
return clusters_list