Source code for nlp_architect.models.cross_doc_coref.sieves_config

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from typing import List, Tuple

from nlp_architect.data.cdc_resources.relations.relation_types_enums import RelationType


[docs]class SievesConfiguration(object): def __init__(self): """Cross document co-reference event and entity evaluation configuration settings""" self.__sieves_order = None self.__run_evaluation = False @property def sieves_order(self): """ Sieve definition and Sieve running order Tuple[SieveType, RelationType, Threshold(float)] - define sieves to run, were Strict- Merge clusters only in case all mentions has current relation between them, Relax- Merge clusters in case (matched mentions) / len(cluster_1.mentions)) >= thresh, Very_Relax- Merge clusters in case (matched mentions) / (all possible pairs) >= thresh RelationType represent the type of sieve to run. """ return self.__sieves_order @sieves_order.setter def sieves_order(self, sieves_order: List[Tuple[RelationType, float]]): self.__sieves_order = sieves_order @property def run_evaluation(self): """Should run evaluation (True/False)""" return self.__run_evaluation @run_evaluation.setter def run_evaluation(self, run_evaluation: bool): self.__run_evaluation = run_evaluation
[docs]class EventSievesConfiguration(SievesConfiguration): def __init__(self): super(EventSievesConfiguration, self).__init__() self.run_evaluation = True self.sieves_order = [ (RelationType.SAME_HEAD_LEMMA, 1.0), (RelationType.EXACT_STRING, 1.0), (RelationType.WIKIPEDIA_DISAMBIGUATION, 0.1), (RelationType.WORD_EMBEDDING_MATCH, 0.7), (RelationType.WIKIPEDIA_REDIRECT_LINK, 0.1), (RelationType.FUZZY_HEAD_FIT, 0.5), (RelationType.FUZZY_FIT, 1.0), (RelationType.WITHIN_DOC_COREF, 1.0), (RelationType.WIKIPEDIA_TITLE_PARENTHESIS, 0.1), (RelationType.WIKIPEDIA_BE_COMP, 0.1), (RelationType.WIKIPEDIA_CATEGORY, 0.1), (RelationType.VERBOCEAN_MATCH, 0.1), (RelationType.WORDNET_DERIVATIONALLY, 1.0) ]
[docs]class EntitySievesConfiguration(SievesConfiguration): def __init__(self): super(EntitySievesConfiguration, self).__init__() self.run_evaluation = True self.sieves_order = [ (RelationType.SAME_HEAD_LEMMA, 1.0), (RelationType.EXACT_STRING, 1.0), (RelationType.FUZZY_FIT, 1.0), (RelationType.WIKIPEDIA_REDIRECT_LINK, 0.1), (RelationType.WIKIPEDIA_DISAMBIGUATION, 0.1), (RelationType.WORD_EMBEDDING_MATCH, 0.7), (RelationType.WORDNET_PARTIAL_SYNSET_MATCH, 0.1), (RelationType.FUZZY_HEAD_FIT, 0.5), (RelationType.WIKIPEDIA_CATEGORY, 0.1), (RelationType.WITHIN_DOC_COREF, 1.0), (RelationType.WIKIPEDIA_BE_COMP, 0.1), (RelationType.WIKIPEDIA_TITLE_PARENTHESIS, 0.1), (RelationType.WORDNET_SAME_SYNSET, 1.0), (RelationType.REFERENT_DICT, 0.5) ]