test_topic_matching_EN.py

import unittest
import holmes_extractor as holmes
from holmes_extractor.topic_matching import TopicMatcher
import os

script_directory = os.path.dirname(os.path.realpath(__file__))
ontology = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')),
                           symmetric_matching=True)
holmes_manager_coref = holmes.Manager(model='en_core_web_trf',
                                      perform_coreference_resolution=True,
                                      ontology=ontology,
                                      number_of_workers=2)



class EnglishTopicMatchingTest(unittest.TestCase):

    def _check_equals(self, text_to_match, document_text, highest_score, manager,
        word_embedding_match_threshold=0.42, use_frequency_factor=True):
        manager.remove_all_documents()
        manager.parse_and_register_document(document_text)
        topic_matches = manager.topic_match_documents_against(text_to_match,
                                                              word_embedding_match_threshold=
                                                              word_embedding_match_threshold,
                                                              relation_score=20,
                                                              reverse_only_relation_score=15, single_word_score=10, single_word_any_tag_score=5,
                                                              different_match_cutoff_score=10,
                                                              relation_matching_frequency_threshold=0.0,
                                                              embedding_matching_frequency_threshold=0.0,
                                                              use_frequency_factor=use_frequency_factor)
        if type(highest_score) == list:
            self.assertIn(int(topic_matches[0]['score']), highest_score)
        else:
            self.assertEqual(int(topic_matches[0]['score']), highest_score)

    def test_no_match(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document("A plant grows")
        topic_matches = holmes_manager_coref.topic_match_documents_against("fewfew",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5)
        self.assertEqual(topic_matches, [])

    def test_no_match_stopwords(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document("then")
        topic_matches = holmes_manager_coref.topic_match_documents_against("then",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5)
        self.assertEqual(topic_matches, [])

    def test_direct_matching(self):
        self._check_equals("A plant grows", "A plant grows",
                           34, holmes_manager_coref)

    def test_direct_matching_frequency_factor_2_word(self):
        self._check_equals("A plant grows", "A plant grows. A plant",
                           34, holmes_manager_coref)

    def test_direct_matching_frequency_factor_3_word(self):
        self._check_equals("A plant grows", "A plant grows. A plant and a plant",
                           16, holmes_manager_coref)

    def test_direct_matching_frequency_factor_3_word_control(self):
        self._check_equals("A plant grows", "A plant grows. A plant and a plant",
                           34, holmes_manager_coref, use_frequency_factor=False)

    def test_direct_matching_frequency_factor_3_word_with_higher_maximum(self):
        self._check_equals("A plant grows", "A plant grows. A plant and a plant. Word word word word word.",
                           22, holmes_manager_coref)

    def test_direct_matching_frequency_factor_2_relation(self):
        self._check_equals("A plant grows", "A plant grows. A plant grows.",
                           34, holmes_manager_coref)

    def test_direct_matching_frequency_factor_3_relation(self):
        self._check_equals("A plant grows", "A plant grows. A plant grows. A plant grows.",
                           8, holmes_manager_coref)

    def test_direct_matching_frequency_factor_3_relation_with_higher_maximum(self):
        self._check_equals("A plant grows", "A plant grows. A plant grows. A plant grows. Word word word word word.",
                           14, holmes_manager_coref)

    def test_direct_matching_nonsense_word(self):
        self._check_equals("A hurricane visited gegwghg", "Peter visited gegwghg", 34,
                           holmes_manager_coref)

    def test_dative_matching(self):
        self._check_equals("I gave Peter a dog",
                           "I gave Peter a present", 34, holmes_manager_coref)

    def test_coref_matching(self):
        self._check_equals("A plant grows", "I saw a plant. It was growing", 34,
                           holmes_manager_coref)

    def test_entity_matching(self):
        self._check_equals("My house visited ENTITYGPE", "Peter visited London", 34,
                           holmes_manager_coref)

    def test_entity_matching_frequency_factor(self):
        self._check_equals("My house visited ENTITYGPE", "Peter visited Paris. Somebody lived in London. Somebody lived in Berlin.", 15,
                           holmes_manager_coref)

    def test_entity_embedding_matching(self):
        self._check_equals("My friend visited ENTITYGPE", "Peter visited London", [56, 57],
                           holmes_manager_coref)

    def test_entity_embedding_matching_frequency_factor(self):
        self._check_equals("My friend visited ENTITYGPE", "Peter visited Paris. Somebody lived in London. Somebody lived in Berlin.", [31, 32],
                           holmes_manager_coref)

    def test_entitynoun_matching(self):
        self._check_equals("My hurricane visited ENTITYNOUN", "Peter visited a city", 25,
                           holmes_manager_coref)

    def test_entitynoun_matching_control(self):
        self._check_equals("My hurricane visited ENTITYNOUN", "Peter visited a city. Word. word.", 25,
                           holmes_manager_coref)

    
    def test_ontology_matching_synonym(self):
        self._check_equals("I saw an pussy", "Somebody saw a cat", 31,
                           holmes_manager_coref)

    
    def test_ontology_matching_synonym_frequency_factor(self):
        self._check_equals("I saw an pussy", "Somebody saw a cat. A cat. A cat.", 14,
                           holmes_manager_coref)

    
    def test_ontology_matching_synonym_frequency_factor_different_ontology_words(self):
        self._check_equals("I saw an pussy", "Somebody saw a cat. A kitten. A cat.", 31,
                           holmes_manager_coref)

    
    def test_ontology_matching_hyponym_depth_1(self):
        self._check_equals("I saw an animal", "Somebody saw a cat", 28,
                           holmes_manager_coref)

    
    def test_ontology_matching_hyponym_depth_1_frequency_factor(self):
        self._check_equals("I saw an animal", "Somebody saw a cat. An cat. A cat.", 13,
                           holmes_manager_coref)

    
    def test_ontology_matching_hyponym_depth_1_frequency_factor_different_ontology_words(self):
        self._check_equals("I saw an animal", "Somebody saw a cat. An kitten. A cat.", 28,
                           holmes_manager_coref)

    
    def test_ontology_matching_hyponym_depth_2(self):
        self._check_equals("I saw an animal", "Somebody saw a kitten", 26,
                           holmes_manager_coref)

    
    def test_ontology_matching_hypernym_depth_1(self):
        self._check_equals("I saw an cat", "Somebody saw an animal", 28,
                           holmes_manager_coref)

    
    def test_ontology_matching_hypernym_depth_2(self):
        self._check_equals("I saw a kitten", "Somebody saw an animal", 26,
                           holmes_manager_coref)

    
    def test_ontology_matching_both_poles(self):
        self._check_equals("A cat opens something", "An animal takes something out", 27,
                           holmes_manager_coref)

    
    def test_ontology_matching_multiword_in_document(self):
        self._check_equals("I saw an animal", "Somebody saw Mimi Momo", 26,
                           holmes_manager_coref)

    
    def test_ontology_matching_multiword_in_document_frequency_factor(self):
        self._check_equals("I saw an animal", "Somebody saw Mimi Momo. Mimi Momo. Mimi Momo.", 12,
                           holmes_manager_coref)

    
    @unittest.skipIf(holmes_manager_coref.nlp.meta['version'] == '3.4.1', 'Version fluke')
    def test_ontology_matching_multiword_in_document_frequency_factor_control(self):
        self._check_equals("I saw an animal", "Somebody saw Mimi Momo. Momo. Momo.", 26,
                           holmes_manager_coref)

    
    def test_ontology_matching_multiword_in_search_text(self):
        self._check_equals("I saw Mimi Momo", "Somebody saw an animal", 26,
                           holmes_manager_coref)

    
    def test_ontology_matching_word_only(self):
        self._check_equals("I saw an animal", "Somebody chased a cat", 8,
                           holmes_manager_coref)

    
    def test_ontology_matching_word_only_multiword_in_document(self):
        self._check_equals("I saw an animal", "Somebody chased Mimi Momo", 7,
                           holmes_manager_coref)

    
    def test_ontology_matching_word_only_multiword_in_search_text(self):
        self._check_equals("I saw Mimi Momo", "Somebody chased an animal", 7,
                           holmes_manager_coref)

    def test_embedding_matching_not_root(self):
        self._check_equals("I saw a king", "Somebody saw a queen", [14, 15],
                           holmes_manager_coref)

    def test_embedding_matching_root_overall_similarity_too_low(self):

        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
        "I saw a king.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("Somebody viewed a queen",
        relation_score=20, reverse_only_relation_score=15, single_word_score=10,
        single_word_any_tag_score=5,
        relation_matching_frequency_threshold=0.0,
        embedding_matching_frequency_threshold=1.0,
        use_frequency_factor=False)
        self.assertEqual(len(topic_matches), 0)

    def test_embedding_matching_root_word_only(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "king")
        topic_matches = holmes_manager_coref.topic_match_documents_against("queen",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.0,
                                                                           embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(len(topic_matches), 0)

    def test_matching_only_adjective(self):
        self._check_equals("nice", "nice", 5, holmes_manager_coref)

    def test_matching_only_adjective_where_noun(self):
        self._check_equals("nice place", "nice", 5, holmes_manager_coref)

    def test_reverse_only_parent_lemma_threeway(self):
        self._check_equals("The donkey has a roof", "The donkey has a roof", 68,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_threeway_coreference(self):
        self._check_equals("A friend has a roof", "I saw a friend and I saw a roof. He had it.", 68,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_twoway(self):
        self._check_equals("The donkey has a roof", "The donkey has a house", [46, 47],
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_threeway_control(self):
        self._check_equals("The donkey paints a roof", "The donkey paints a roof", 82,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_twoway_control(self):
        self._check_equals("The donkey paints a roof", "The donkey paints a house", [56, 58],
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_twoway_control_no_embedding_based_match(self):
        self._check_equals("The donkey paints a roof", "The donkey paints a mouse", 34,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_be(self):
        self._check_equals("A president is a politician", "A president is a politician", 68,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_be_reversed(self):
        self._check_equals("A president is a politician", "A politician is a president", 24,
                           holmes_manager_coref)

    def test_reverse_only_parent_lemma_aux_in_document(self):
        self._check_equals("A donkey has a roof", "A donkey has painted a roof", 24,
                           holmes_manager_coref)

    def test_reverse_matching_noun_no_coreference(self):
        self._check_equals("A car with an engine", "An automobile with an engine", [50, 51],
                           holmes_manager_coref)

    def test_reverse_matching_noun_no_coreference_frequency_factor(self):
        self._check_equals("A car with an engine", "An automobile with an engine. An engine. An engine.", [27, 28],
                           holmes_manager_coref)

    def test_reverse_matching_noun_no_coreference_control_no_embeddings(self):
        self._check_equals("A car with an engine", "An automobile with an engine", 29,
                           holmes_manager_coref, word_embedding_match_threshold=1.0)

    def test_reverse_matching_noun_no_coreference_control_same_word(self):
        self._check_equals("A car with an engine", "A car with an engine", 75,
                           holmes_manager_coref, word_embedding_match_threshold=1.0)

    def test_forward_matching_noun_entity_governor_match(self):
        self._check_equals("An ENTITYPERSON with a car", "Richard Hudson with a vehicle", [23, 24],
                           holmes_manager_coref)

    def test_forward_matching_noun_entity_governor_no_match(self):
        self._check_equals("An ENTITYPERSON with a car", "Richard Hudson with a lion", 14,
                           holmes_manager_coref)

    def test_reverse_matching_noun_entity_governed(self):
        self._check_equals("A car with an ENTITYPERSON", "A vehicle with Richard Hudson", 50,
                           holmes_manager_coref)

    def test_forward_matching_noun_entitynoun_governor_match(self):
        self._check_equals("An ENTITYNOUN with a car", "Richard Hudson with a vehicle", 5,
                           holmes_manager_coref)

    def test_forward_matching_noun_entitynoun_governor_no_match(self):
        self._check_equals("An ENTITYNOUN with a car", "Richard Hudson with a lion", 5,
                           holmes_manager_coref)

    def test_reverse_matching_noun_entitynoun_governed(self):
        self._check_equals("A car with an ENTITYNOUN", "A vehicle with Richard Hudson", 5,
                           holmes_manager_coref)

    def test_multiword_matching_with_hyphen_normalization(self):
        self._check_equals("Richard Hudson speaks", "Richard-Hudson speaks",
                           34, holmes_manager_coref)

    def test_relation_matching_suppressed(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document("A dog chases a cat. A dog sees a cat. A dog sees a cat. A person was chasing a person. A person chased a person.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A dog chases a cat.",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=1.0,
                                                                           embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 24)

    def test_suppressed_relation_matching_picked_up_during_reverse_matching(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "Chasing. Chasing. A dog chases a cat. A lion chases a tiger.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A dog chases a cat",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.9,
                                                                           embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 82)

    def test_suppressed_relation_matching_picked_up_during_reverse_matching_with_coreference(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "There was a cat. A dog chased it. A lion chases a tiger. Chasing. Chasing. ")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A dog chases a cat",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.9,
                                                                           embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 84)

    def test_suppressed_relation_matching_picked_up_during_reverse_matching_with_reverse_dependency(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "Someone adopts the child. The child is here. Children. Children. Children.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("An adopted child",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.9,
                                                                           embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)

        self.assertEqual(int(topic_matches[0]['score']), 34)

    def test_reverse_matching_suppressed_with_relation_matching(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I was in Germany. I know Germany. Germany. Germany.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("in Germany",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.1, embedding_matching_frequency_threshold=0.6)
        self.assertEqual(int(topic_matches[0]['score']), 10)

    def test_reverse_matching_suppressed_with_relation_matching_embedding_value_same(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I was in Germany. I know Germany. Germany. Germany.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("in Germany",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.1, embedding_matching_frequency_threshold=0.1)
        self.assertEqual(int(topic_matches[0]['score']), 10)

    def test_reverse_matching_suppressed_with_relation_matching_control(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I was in Germany. I know Germany. Germany. Germany.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("in Germany",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=1.0, embedding_matching_frequency_threshold=1.0)
        self.assertEqual(int(topic_matches[0]['score']), 7)

    def test_reverse_matching_suppressed_with_embedding_reverse_matching_parent(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "An automobile with an engine. An engine. An engine.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A car with an engine",
                                                                           word_embedding_match_threshold=0.42,
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.0, embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 29)

    def test_reverse_matching_suppressed_with_embedding_reverse_matching_parent_control(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "An automobile with an engine. An engine. An engine.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A car with an engine",
                                                                           word_embedding_match_threshold=0.42,
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.0, embedding_matching_frequency_threshold=0.0,
                                                                           use_frequency_factor=False)
        self.assertIn(int(topic_matches[0]['score']), [50, 51])

    def test_reverse_matching_suppressed_with_embedding_reverse_matching_child(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "An engine with an automobile. An engine. An engine.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("An engine with a car",
                                                                           word_embedding_match_threshold=0.42,
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=1.0, embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 14)

    def test_reverse_matching_suppressed_with_embedding_reverse_matching_child_control(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "An engine with an automobile. An engine. An engine.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("An engine with a car",
                                                                           word_embedding_match_threshold=0.42,
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.0, embedding_matching_frequency_threshold=0.0,
                                                                           use_frequency_factor=False)
        self.assertIn(int(topic_matches[0]['score']), [24, 25])

    def test_entity_matching_suppressed_with_relation_matching_for_governor(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I was tired Richard Paul Hudson. I was a tired Richard Paul Hudson. I spoke to Richard Paul Hudson and he was tired.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("tired ENTITYPERSON",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=1.0, embedding_matching_frequency_threshold=1.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 14)

    def test_entity_matching_suppressed_with_relation_matching_for_governor_control(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I was tired Richard Paul Hudson. I was a tired Richard Paul Hudson. I spoke to Richard Paul Hudson and he was tired.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("tired ENTITYPERSON",
                                                                           relation_score=20, reverse_only_relation_score=15, single_word_score=10,
                                                                           single_word_any_tag_score=5,
                                                                           relation_matching_frequency_threshold=0.0, embedding_matching_frequency_threshold=0.0,
                                                                           use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 34)

    def test_entity_matching_suppressed_with_relation_matching_for_governed(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I knew Richard Paul Hudson. I knew Richard Paul Hudson. I knew someone and spoke to Richard Paul Hudson.")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "someone knows an ENTITYPERSON",
            relation_score=20, reverse_only_relation_score=15, single_word_score=10,
            single_word_any_tag_score=5,
            relation_matching_frequency_threshold=1.0,
            embedding_matching_frequency_threshold=1.0,
            use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 14)

    def test_entity_matching_suppressed_with_relation_matching_for_governed_control(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I knew Richard Paul Hudson. I knew Richard Paul Hudson. I knew someone and spoke to Richard Paul Hudson.")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "someone knows an ENTITYPERSON",
            relation_score=20, reverse_only_relation_score=15, single_word_score=10,
            single_word_any_tag_score=5,
            relation_matching_frequency_threshold=0.0,
            embedding_matching_frequency_threshold=0.0,
            use_frequency_factor=False)
        self.assertEqual(int(topic_matches[0]['score']), 34)

    def test_reverse_matching_noun_coreference_on_governor(self):
        self._check_equals("A car with an engine", "I saw an automobile. I saw it with an engine",
                           [50, 51],
                           holmes_manager_coref)

    def test_reverse_matching_noun_coreference_on_governor_control_no_embeddings(self):
        self._check_equals("A car with an engine", "I saw an automobile. I saw it with an engine",
                           29,
                           holmes_manager_coref, word_embedding_match_threshold=1.0)

    @unittest.skipIf(holmes_manager_coref.nlp.meta['version'] == '3.5.0', 'Version fluke')
    def test_reverse_matching_noun_coreference_on_governor_control_same_word(self):
        self._check_equals("A car with an engine", "I saw a car. I saw it with an engine",
                           73,
                           holmes_manager_coref, word_embedding_match_threshold=1.0)

    def test_reverse_matching_noun_coreference_on_governed(self):
        self._check_equals(
            "An engine with a car", "I saw an automobile. I saw the engine with it", [24, 25],
            holmes_manager_coref)

    def test_reverse_matching_noun_coreference_on_governed_control_no_embeddings(self):
        self._check_equals(
            "An engine with a car", "I saw an automobile. I saw the engine with it", 14,
            holmes_manager_coref, word_embedding_match_threshold=1.0)

    def test_reverse_matching_noun_coreference_on_governed_control_same_word(self):
        self._check_equals(
            "An engine with a car", "I saw a car. I saw the engine with it", 76,
            holmes_manager_coref, word_embedding_match_threshold=1.0)

    def test_reverse_matching_verb_with_coreference_and_conjunction(self):
        self._check_equals("A company is bought", "A company is bought and purchased", 34,
                           holmes_manager_coref)

    def test_two_matches_on_same_document_tokens_because_of_embeddings(self):
        self._check_equals("Somebody buys a vehicle",
                           "Somebody buys a vehicle and a car", 34,
                           holmes_manager_coref)

    def test_reverse_matching_only(self):
        self._check_equals("with an idea",
                           "with an idea", 29,
                           holmes_manager_coref)

    def test_repeated_single_word_label_tags_matched(self):
        self._check_equals("dog",
                           "a dog and a dog", 10,
                           holmes_manager_coref)

    def test_repeated_single_word_label_tags_not_matched(self):
        self._check_equals("in",
                           "in and in", 5,
                           holmes_manager_coref)

    def test_repeated_relation_label_not_reverse_only_no_common_term(self):
        self._check_equals("a big dog",
                           "a big dog and a big dog", 34,
                           holmes_manager_coref)

    def test_repeated_relation_label_not_reverse_only_common_term(self):
        self._check_equals("a big dog",
                           "a big and big dog", 34,
                           holmes_manager_coref)

    def test_repeated_relation_label_reverse_only_no_common_term(self):
        self._check_equals("in Germany",
                           "in Germany and in Germany", 29,
                           holmes_manager_coref)

    def test_repeated_relation_label_reverse_only_common_term(self):
        self._check_equals("in Germany",
                           "in Germany and Germany", 29,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_not_root(self):
        self._check_equals("Richard Paul Hudson came",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_single_word_in_document_not_root(self):
        self._check_equals("Hudson came",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_dependent_words_in_document_not_root(self):
        self._check_equals("Richard Paul came",
                           "I saw Richard Paul Hudson", 9,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_multiword_in_document_with_coref_not_root(self):
        self._check_equals("Richard Paul Hudson came",
                           "I saw Richard Paul Hudson. He came", 34,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_multiword_in_document_with_noun_coref_not_root(self):
        self._check_equals("Richard Paul Hudson came",
                           "I saw Richard Paul Hudson. Hudson came", 39,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_single_in_document_with_coref_not_root(self):
        self._check_equals("Hudson came",
                           "I saw Richard Paul Hudson. He came", 34,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_root(self):
        self._check_equals("the tired Richard Paul Hudson",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_single_word_in_document_root(self):
        self._check_equals("the tired Hudson",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_dependent_words_in_document_root(self):
        self._check_equals("the tired Richard Paul",
                           "I saw Richard Paul Hudson", 9,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_multiword_in_document_with_coref_root(self):
        self._check_equals("the tired Richard Paul Hudson",
                           "I saw Richard Paul Hudson. He came", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_single_in_document_with_coref_root(self):
        self._check_equals("the tired Hudson came",
                           "I saw Richard Paul Hudson. He came", 34,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_not_root_match_on_embeddings(self):
        self._check_equals("Richard Paul Hudson came",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_root_match_on_embeddings(self):
        self._check_equals("the tired Richard Paul Hudson",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_not_root_no_embeddings(self):
        self._check_equals("Richard Paul Hudson came",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_multiword_in_text_to_search_and_in_document_root_no_embeddings(self):
        self._check_equals("the tired Richard Paul Hudson",
                           "I saw Richard Paul Hudson", 10,
                           holmes_manager_coref)

    def test_matches_in_opposite_directions(self):
        self._check_equals("the mirror of Erised",
                           "the mirror of Erised", 39,
                           holmes_manager_coref)

    def test_derived_form_text_to_match_single_word(self):
        self._check_equals("information",
                           "inform", 10,
                           holmes_manager_coref)

    def test_derived_form_text_to_match_single_word_frequency_factor(self):
        self._check_equals("information",
                           "inform. inform. inform.", 3,
                           holmes_manager_coref)

    def test_derived_form_document_text_single_word(self):
        self._check_equals("give",
                           "gift", 5,
                           holmes_manager_coref)

    def test_derived_form_single_word_control(self):
        self._check_equals("information",
                           "information", 10,
                           holmes_manager_coref)

    def test_derived_form_document_text_parent(self):
        self._check_equals("inform quickly",
                           "quick information", 29,
                           holmes_manager_coref)

    def test_derived_form_text_to_match_parent(self):
        self._check_equals("quick information",
                           "inform quickly", 34,
                           holmes_manager_coref)

    def test_derived_form_parent_control(self):
        self._check_equals("quick information",
                           "quick information", 34,
                           holmes_manager_coref)

    def test_derived_form_document_text_child(self):
        self._check_equals("He decided to inform",
                           "He decided information", 29,
                           holmes_manager_coref)

    def test_derived_form_text_to_match_child(self):
        self._check_equals("He decided information",
                           "He decided to inform", 34,
                           holmes_manager_coref)

    def test_derived_form_child_control(self):
        self._check_equals("He decided information",
                           "He decided information", 34,
                           holmes_manager_coref)

    
    def test_derived_forms_matched_by_ontology_1(self):
        self._check_equals("An invitation to a politician",
                           "He explained to a politician", 35,
                           holmes_manager_coref)

    
    def test_derived_forms_matched_by_ontology_2(self):
        self._check_equals("He explained to a politician",
                           "An invitation to a politician", 31,
                           holmes_manager_coref)

    
    def test_derived_multiword_child_also_matched_by_ontology_1(self):
        self._check_equals("He used a waste horse",
                           "He used a wastage horse", 34,
                           holmes_manager_coref)

    
    def test_derived_multiword_child_also_matched_by_ontology_2(self):
        self._check_equals("He used a wastage horse",
                           "He used a waste horse", 33,
                           holmes_manager_coref)

    
    def test_derived_multiword_child_also_matched_by_ontology_3(self):
        self._check_equals("He used a waste horse",
                           "He used gymnastics equipment", 26,
                           holmes_manager_coref)

    
    def test_derived_multiword_child_also_matched_by_ontology_4(self):
        self._check_equals("He used gymnastics equipment",
                           "He used a waste horse", 26,
                           holmes_manager_coref)

    
    def test_derived_multiword_parent_also_matched_by_ontology_1(self):
        self._check_equals("A big waste horse",
                           "A big wastage horse", 34,
                           holmes_manager_coref)

    
    def test_derived_multiword_parent_also_matched_by_ontology_2(self):
        self._check_equals("A big wastage horse",
                           "A big waste horse", 34,
                           holmes_manager_coref)

    
    def test_derived_multiword_parent_also_matched_by_ontology_3(self):
        self._check_equals("A big waste horse",
                           "A big gymnastics equipment", 26,
                           holmes_manager_coref)

    
    def test_derived_multiword_parent_also_matched_by_ontology_4(self):
        self._check_equals("A big gymnastics equipment",
                           "A big waste horse", 26,
                           holmes_manager_coref)

    def test_reverse_dependencies_1(self):
        self._check_equals("An adopted child",
                           "Someone adopts a child", 34,
                           holmes_manager_coref)

    def test_reverse_dependencies_2(self):
        self._check_equals("Someone adopts a child",
                           "An adopted child", 34,
                           holmes_manager_coref)

    def test_reverse_dependencies_control(self):
        self._check_equals("Adopted and child",
                           "An adopted child", 14,
                           holmes_manager_coref)

    def test_tough_movement(self):
        self._check_equals("A leg is hard to stretch", "He stretched his legs.",
                           34,
                           holmes_manager_coref)

    def test_tough_movement_control(self):
        self._check_equals("A leg is hard to fix", "He stretched his legs.",
                           10,
                           holmes_manager_coref)

    def test_coreference_double_match_on_governed(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I saw a man. The man walked")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A man walks",
                                                                           relation_score=20, single_word_score=10, single_word_any_tag_score=5)
        self.assertEqual(int(topic_matches[0]['score']), 34)
        self.assertEqual(topic_matches[0]['sentences_start_index'], 5)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 7)
        self.assertEqual(topic_matches[0]['start_index'], 6)
        self.assertEqual(topic_matches[0]['end_index'], 7)

    def test_coreference_double_match_on_governor(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I saw a big man. The man walked")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "A big man", relation_score=20, single_word_score=10, single_word_any_tag_score=5)
        self.assertEqual(int(topic_matches[0]['score']), 34)
        self.assertEqual(topic_matches[0]['sentences_start_index'], 0)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 8)
        self.assertEqual(topic_matches[0]['start_index'], 3)
        self.assertEqual(topic_matches[0]['end_index'], 7)

    def test_coreference_double_match_same_distance(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "The man was big. Man walked.")
        topic_matches = holmes_manager_coref.topic_match_documents_against("A big man",
                                                                           relation_score=20, single_word_score=10, single_word_any_tag_score=5)
        self.assertEqual(int(topic_matches[0]['score']), 34)
        self.assertEqual(topic_matches[0]['sentences_start_index'], 0)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 7)
        self.assertEqual(topic_matches[0]['start_index'], 1)
        self.assertEqual(topic_matches[0]['end_index'], 5)

    def test_indexes(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "This is an irrelevant sentence. I think a plant grows.")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "A plant grows")
        self.assertEqual(topic_matches[0]['sentences_start_index'], 6)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 11)
        self.assertEqual(topic_matches[0]['start_index'], 9)
        self.assertEqual(topic_matches[0]['end_index'], 10)

    def test_indexes_with_preceding_non_matched_dependent(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "I saw a big dog.")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "A big dog")
        self.assertEqual(topic_matches[0]['sentences_start_index'], 0)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 5)
        self.assertEqual(topic_matches[0]['start_index'], 3)
        self.assertEqual(topic_matches[0]['end_index'], 4)

    def test_indexes_with_subsequent_non_matched_dependent(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.parse_and_register_document(
            "The dog I saw was big.")
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "A big dog")
        self.assertEqual(topic_matches[0]['sentences_start_index'], 0)
        self.assertEqual(topic_matches[0]['sentences_end_index'], 6)
        self.assertEqual(topic_matches[0]['start_index'], 1)
        self.assertEqual(topic_matches[0]['end_index'], 5)

    def test_only_one_result_per_document(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            """
                Peter came home. A great deal of irrelevant text. A great deal of irrelevant text.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. Peter came home.
                """)
        self.assertEqual(
            len(holmes_manager_coref.topic_match_documents_against("Peter")), 2)
        self.assertEqual(len(holmes_manager_coref.topic_match_documents_against("Peter",
                                                                                only_one_result_per_document=True)), 1)

    def test_match_cutoff(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            """
                A cat.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
                A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
                irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
                The dog chased the cat.
                """)
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "The dog chased the cat")
        self.assertEqual(topic_matches[0]['start_index'], 117)
        self.assertEqual(topic_matches[0]['end_index'], 120)

    def test_result_ordering_by_match_length_different_documents_2(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document("""
        A dog chased a cat.
        A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
        irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
        A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
        irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
        A great deal of irrelevant text. A great deal of irrelevant text. A great deal of
        irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text.
        A dog chased a cat. A cat
        """)
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "The dog chased the cat")
        self.assertEqual(
            topic_matches[0]['end_index'] - topic_matches[0]['start_index'], 6)
        self.assertEqual(
            topic_matches[1]['end_index'] - topic_matches[1]['start_index'], 3)

    def test_dictionaries(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document("A dog chased a cat. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A great deal of irrelevant text. A dog chased a cat. A cat. Another irrelevant sentence.")
        holmes_manager_coref.parse_and_register_document("Dogs and cats.",
                                                         "animals")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", use_frequency_factor=False)
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'A dog chased a cat. A cat.', 'text_to_match': 'The dog chased the cat', 'rank': '1=', 'index_within_document': 115, 'subword_index': None, 'start_index': 112, 'end_index': 118, 'sentences_start_index': 111, 'sentences_end_index': 119, 'sentences_character_start_index': 515, 'sentences_character_end_index': 541, 'score': 993.4666666666667, 'word_infos': [[2, 5, 'overlapping_relation', False, 'Matches DOG directly.'], [6, 12, 'overlapping_relation', False, 'Matches CHASE directly.'], [15, 18, 'overlapping_relation', True, 'Matches CAT directly.'], [22, 25, 'single', False, 'Matches CAT directly.']], 'answers': []}, {'document_label': '', 'text': 'A dog chased a cat.', 'text_to_match': 'The dog chased the cat', 'rank': '1=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 5, 'sentences_character_start_index': 0, 'sentences_character_end_index': 19, 'score': 993.4666666666667, 'word_infos': [[2, 5, 'overlapping_relation', False, 'Matches DOG directly.'], [6, 12, 'overlapping_relation', False, 'Matches CHASE directly.'], [15, 18, 'overlapping_relation', True, 'Matches CAT directly.']], 'answers': []}, {'document_label': 'animals', 'text': 'Dogs and cats.', 'text_to_match': 'The dog chased the cat', 'rank': '3', 'index_within_document': 2, 'subword_index': None, 'start_index': 0, 'end_index': 2, 'sentences_start_index': 0, 'sentences_end_index': 3, 'sentences_character_start_index': 0, 'sentences_character_end_index': 14, 'score': 98.66666666666667, 'word_infos': [[0, 4, 'single', False, 'Matches DOG directly.'], [9, 13, 'single', True, 'Matches CAT directly.']], 'answers': []}])
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", tied_result_quotient=0.01, use_frequency_factor=False)
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'A dog chased a cat. A cat.', 'text_to_match': 'The dog chased the cat', 'rank': '1=', 'index_within_document': 115, 'subword_index': None, 'start_index': 112, 'end_index': 118, 'sentences_start_index': 111, 'sentences_end_index': 119, 'sentences_character_start_index': 515, 'sentences_character_end_index': 541, 'score': 993.4666666666667, 'word_infos': [[2, 5, 'overlapping_relation', False, 'Matches DOG directly.'], [6, 12, 'overlapping_relation', False, 'Matches CHASE directly.'], [15, 18, 'overlapping_relation', True, 'Matches CAT directly.'], [22, 25, 'single', False, 'Matches CAT directly.']], 'answers': []}, {'document_label': '', 'text': 'A dog chased a cat.', 'text_to_match': 'The dog chased the cat', 'rank': '1=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 5, 'sentences_character_start_index': 0, 'sentences_character_end_index': 19, 'score': 993.4666666666667, 'word_infos': [[2, 5, 'overlapping_relation', False, 'Matches DOG directly.'], [6, 12, 'overlapping_relation', False, 'Matches CHASE directly.'], [15, 18, 'overlapping_relation', True, 'Matches CAT directly.']], 'answers': []}, {'document_label': 'animals', 'text': 'Dogs and cats.', 'text_to_match': 'The dog chased the cat', 'rank': '1=', 'index_within_document': 2, 'subword_index': None, 'start_index': 0, 'end_index': 2, 'sentences_start_index': 0, 'sentences_end_index': 3, 'sentences_character_start_index': 0, 'sentences_character_end_index': 14, 'score': 98.66666666666667, 'word_infos': [[0, 4, 'single', False, 'Matches DOG directly.'], [9, 13, 'single', True, 'Matches CAT directly.']], 'answers': []}])

    def test_dictionaries_with_multiword_in_relation_not_final(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "Richard Paul Hudson came home")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "Richard Paul Hudson was coming")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'Richard Paul Hudson came home', 'text_to_match': 'Richard Paul Hudson was coming', 'rank': '1', 'index_within_document': 3, 'subword_index': None, 'start_index': 0, 'end_index': 3, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 29, 'score': 369.3333333333333, 'word_infos': [[0, 19, 'relation', False, 'Matches RICHARD PAUL HUDSON directly.'], [20, 24, 'relation', True, 'Matches COME directly.']], 'answers': []}])

    def test_dictionaries_with_multiword_alone(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document("Richard Paul Hudson")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "Richard Paul Hudson")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'Richard Paul Hudson', 'text_to_match': 'Richard Paul Hudson', 'rank': '1', 'index_within_document': 2, 'subword_index': None, 'start_index': 0, 'end_index': 2, 'sentences_start_index': 0, 'sentences_end_index': 2, 'sentences_character_start_index': 0, 'sentences_character_end_index': 19, 'score': 50, 'word_infos': [[0, 19, 'single', True, 'Matches RICHARD PAUL HUDSON directly.']], 'answers': []}])

    def test_dictionaries_with_multiword_alone_and_entity_token_in_text_to_match(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document("Richard Paul Hudson")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "ENTITYPERSON")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'Richard Paul Hudson', 'text_to_match': 'ENTITYPERSON', 'rank': '1', 'index_within_document': 2, 'subword_index': None, 'start_index': 0, 'end_index': 2, 'sentences_start_index': 0, 'sentences_end_index': 2, 'sentences_character_start_index': 0, 'sentences_character_end_index': 19, 'score': 50.0, 'word_infos': [[0, 19, 'single', True, 'Has an entity label matching ENTITYPERSON.']], 'answers': []}])

    
    def test_dictionaries_with_multiword_as_single_word_and_relation(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "Can somebody give Harry Potter his present")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "Somebody gives a present to Harry")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'Can somebody give Harry Potter his present', 'text_to_match': 'Somebody gives a present to Harry', 'rank': '1', 'index_within_document': 6, 'subword_index': None, 'start_index': 2, 'end_index': 6, 'sentences_start_index': 0, 'sentences_end_index': 6, 'sentences_character_start_index': 0, 'sentences_character_end_index': 42, 'score': 922.1333333333332, 'word_infos': [[13, 17, 'overlapping_relation', False, 'Matches GIVE directly.'], [18, 30, 'overlapping_relation', False, 'Is a synonym of HARRY in the ontology.'], [35, 42, 'overlapping_relation', True, 'Matches PRESENT directly.']], 'answers': []}])

    def test_result_ordering_by_match_length_different_documents_1(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A dog chased a cat.", '1')
        holmes_manager_coref.parse_and_register_document(
            "A dog chased a cat. A cat.", '2')
        topic_matches = holmes_manager_coref.topic_match_documents_against(
            "The dog chased the cat")
        self.assertEqual(topic_matches[0]['end_index'], 7)
        self.assertEqual(topic_matches[1]['end_index'], 4)

    def test_filtering_with_topic_matches(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T11")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T12")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T21")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T22")
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat")
        self.assertEqual(len(topic_matches), 4)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T")
        self.assertEqual(len(topic_matches), 4)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T1")
        self.assertEqual(len(topic_matches), 2)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T22")
        self.assertEqual(len(topic_matches), 1)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="X")
        self.assertEqual(len(topic_matches), 0)

    def test_filtering_with_topic_match_dictionaries(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T11")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T12")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T21")
        holmes_manager_coref.parse_and_register_document(
            "The dog chased the cat", "T22")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat")
        self.assertEqual(len(topic_match_dictionaries), 4)
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T")
        self.assertEqual(len(topic_match_dictionaries), 4)
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T1")
        self.assertEqual(len(topic_match_dictionaries), 2)
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T22")
        self.assertEqual(len(topic_match_dictionaries), 1)
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="X")
        self.assertEqual(len(topic_match_dictionaries), 0)

    
    def test_adjective_describing_ontology_multiword_with_topic_match_dictionaries(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A big Unhyphenated Single Multiword")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A big Unhyphenated Single Multiword")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'A big Unhyphenated Single Multiword', 'text_to_match': 'A big Unhyphenated Single Multiword', 'rank': '1', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 35, 'score': 369.2, 'word_infos': [[2, 5, 'relation', False, 'Matches BIG directly.'], [6, 35, 'relation', True, 'Matches UNHYPHENATED SINGLE MULTIWORD directly.']], 'answers': []}])

    def test_adjective_describing_entity_multiword_with_topic_match_dictionaries(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A big Richard Paul Hudson")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A big Richard Paul Hudson")
        self.assertEqual(topic_match_dictionaries,
                        [{'document_label': '', 'text': 'A big Richard Paul Hudson', 'text_to_match': 'A big Richard Paul Hudson', 'rank': '1', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 369.2, 'word_infos': [[2, 5, 'relation', False, 'Matches BIG directly.'], [6, 25, 'relation', True, 'Matches RICHARD PAUL HUDSON directly.']], 'answers': []}])

    
    def test_adjective_describing_double_multiword_with_topic_match_dictionaries_1(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A big Richard Pranaya Jones")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A big Richard Pranaya Jones")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'A big Richard Pranaya Jones', 'text_to_match': 'A big Richard Pranaya Jones', 'rank': '1', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 27, 'score': 1017.8666666666667, 'word_infos': [[2, 5, 'overlapping_relation', False, 'Matches BIG directly.'], [6, 13, 'overlapping_relation', False, 'Matches RICHARD directly.'], [14, 27, 'overlapping_relation', True, 'Matches PRANAYA JONES directly.']], 'answers': []}])

    
    def test_adjective_describing_double_multiword_with_topic_match_dictionaries_2(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A big Richard Pranaya Jones")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A big Pranaya Jones")
        self.assertEqual(topic_match_dictionaries,
                          [{'document_label': '', 'text': 'A big Richard Pranaya Jones', 'text_to_match': 'A big Pranaya Jones', 'rank': '1', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 27, 'score': 369.2, 'word_infos': [[2, 5, 'relation', False, 'Matches BIG directly.'], [14, 27, 'relation', True, 'Matches PRANAYA JONES directly.']], 'answers': []}])

    
    def test_adjective_describing_double_multiword_with_topic_match_dictionaries_3(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A big Richard Pranaya Jones")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A big Jones")
        self.assertEqual(topic_match_dictionaries,
                         [{'document_label': '', 'text': 'A big Richard Pranaya Jones', 'text_to_match': 'A big Jones', 'rank': '1', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 27, 'score': 369.2, 'word_infos': [[2, 5, 'relation', False, 'Matches BIG directly.'], [22, 27, 'relation', True, 'Matches JONES directly.']], 'answers': []}])

    def test_different_match_cutoff_score_low(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A dog and a dog then and then and then and then and then a dog")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog")
        self.assertEqual(len(topic_match_dictionaries), 1)

    def test_different_match_cutoff_score_high_1(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A dog then and then and then and then and then a dog")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog", different_match_cutoff_score=10000)
        self.assertEqual(len(topic_match_dictionaries), 2)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog", different_match_cutoff_score=10000)
        self.assertEqual(len(topic_matches), 2)

    def test_different_match_cutoff_score_zero(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A dog then and then and then and then and then a dog")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog", different_match_cutoff_score=0)
        self.assertEqual(len(topic_match_dictionaries), 1)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog", different_match_cutoff_score=0)
        self.assertEqual(len(topic_matches), 1)


    def test_different_match_cutoff_score_control_1(self):
        holmes_manager_coref.remove_all_documents()
        holmes_manager_coref.remove_all_search_phrases()
        holmes_manager_coref.parse_and_register_document(
            "A dog then and then and then and then and then a dog")
        topic_match_dictionaries = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog")
        self.assertEqual(len(topic_match_dictionaries), 1)
        topic_matches = \
            holmes_manager_coref.topic_match_documents_against(
                "A dog")
        self.assertEqual(len(topic_matches), 1)

    
    def test_one_worker_frequency_factor(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', ontology=ontology_for_sm_tests,
            number_of_workers=1)
        m.parse_and_register_document("I saw a dog. It was chasing a cat", 'specific')
        m.parse_and_register_document("The dog chased the animal", 'exact')
        m.parse_and_register_document("The cat chased the dog", 'specific-reversed')
        m.parse_and_register_document("The animal chased the dog", 'exact-reversed')
        self.assertEqual(m.list_document_labels(), ['exact', 'exact-reversed', 'specific',
                                               'specific-reversed'])
        self.assertEqual(m.topic_match_documents_against(
            "A dog chases an animal",
            relation_score=30,
            reverse_only_relation_score=20,
            single_word_score=5,
            single_word_any_tag_score=2,
            different_match_cutoff_score=5,
            relation_matching_frequency_threshold=0.2),
            [{'document_label': 'exact', 'text': 'The dog chased the animal', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 17.654017250803907, 'word_infos': [[4, 7, 'overlapping_relation', False, 'Matches DOG directly.'], [8, 14, 'overlapping_relation', False, 'Matches CHASE directly.'], [19, 25, 'overlapping_relation', True, 'Matches ANIMAL directly.']], 'answers': []}, {'document_label': 'specific', 'text': 'I saw a dog. It was chasing a cat', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 9, 'subword_index': None, 'start_index': 3, 'end_index': 9, 'sentences_start_index': 0, 'sentences_end_index': 9, 'sentences_character_start_index': 0, 'sentences_character_end_index': 33, 'score': 15.963706826344412, 'word_infos': [[8, 11, 'overlapping_relation', False, 'Matches DOG directly.'], [20, 27, 'overlapping_relation', False, 'Matches CHASE directly.'], [30, 33, 'overlapping_relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}, {'document_label': 'exact-reversed', 'text': 'The animal chased the dog', 'text_to_match': 'A dog chases an animal', 'rank': '3=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 8.083873269940398, 'word_infos': [[4, 10, 'single', False, 'Matches ANIMAL directly.'], [11, 17, 'relation', False, 'Matches CHASE directly.'], [22, 25, 'relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}, {'document_label': 'specific-reversed', 'text': 'The cat chased the dog', 'text_to_match': 'A dog chases an animal', 'rank': '3=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 22, 'score': 7.731063509742494, 'word_infos': [[4, 7, 'single', False, 'Is a child of ANIMAL in the ontology.'], [8, 14, 'relation', False, 'Matches CHASE directly.'], [19, 22, 'relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}])
        m.close()

    
    def test_two_workers_frequency_factor_control(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', ontology=ontology_for_sm_tests, number_of_workers=2)
        m.parse_and_register_document("I saw a dog. It was chasing a cat", 'specific')
        m.parse_and_register_document("The dog chased the animal", 'exact')
        m.parse_and_register_document("The cat chased the dog", 'specific-reversed')
        m.parse_and_register_document("The animal chased the dog", 'exact-reversed')
        self.assertEqual(m.list_document_labels(), ['exact', 'exact-reversed', 'specific',
                                               'specific-reversed'])
        self.assertEqual(m.topic_match_documents_against(
            "A dog chases an animal",
            relation_score=30,
            reverse_only_relation_score=20,
            single_word_score=5,
            single_word_any_tag_score=2,
            different_match_cutoff_score=5,
            relation_matching_frequency_threshold=0.2),
            [{'document_label': 'exact', 'text': 'The dog chased the animal', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 17.654017250803907, 'word_infos': [[4, 7, 'overlapping_relation', False, 'Matches DOG directly.'], [8, 14, 'overlapping_relation', False, 'Matches CHASE directly.'], [19, 25, 'overlapping_relation', True, 'Matches ANIMAL directly.']], 'answers': []}, {'document_label': 'specific', 'text': 'I saw a dog. It was chasing a cat', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 9, 'subword_index': None, 'start_index': 3, 'end_index': 9, 'sentences_start_index': 0, 'sentences_end_index': 9, 'sentences_character_start_index': 0, 'sentences_character_end_index': 33, 'score': 15.963706826344412, 'word_infos': [[8, 11, 'overlapping_relation', False, 'Matches DOG directly.'], [20, 27, 'overlapping_relation', False, 'Matches CHASE directly.'], [30, 33, 'overlapping_relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}, {'document_label': 'exact-reversed', 'text': 'The animal chased the dog', 'text_to_match': 'A dog chases an animal', 'rank': '3=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 8.083873269940398, 'word_infos': [[4, 10, 'single', False, 'Matches ANIMAL directly.'], [11, 17, 'relation', False, 'Matches CHASE directly.'], [22, 25, 'relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}, {'document_label': 'specific-reversed', 'text': 'The cat chased the dog', 'text_to_match': 'A dog chases an animal', 'rank': '3=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 22, 'score': 7.731063509742494, 'word_infos': [[4, 7, 'single', False, 'Is a child of ANIMAL in the ontology.'], [8, 14, 'relation', False, 'Matches CHASE directly.'], [19, 22, 'relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}])
        m.close()

    
    def test_number_of_results(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', ontology=ontology_for_sm_tests,
            number_of_workers=2)
        m.parse_and_register_document("I saw a dog. It was chasing a cat", 'specific')
        m.parse_and_register_document("The dog chased the animal", 'exact')
        m.parse_and_register_document("The cat chased the dog", 'specific-reversed')
        m.parse_and_register_document("The animal chased the dog", 'exact-reversed')
        self.assertEqual(m.list_document_labels(), ['exact', 'exact-reversed', 'specific',
                                               'specific-reversed'])
        self.assertEqual(m.topic_match_documents_against(
            "A dog chases an animal", number_of_results=3, use_frequency_factor=True,
            relation_score=30,
            reverse_only_relation_score=20,
            single_word_score=5,
            single_word_any_tag_score=2,
            different_match_cutoff_score=5,
            relation_matching_frequency_threshold=0.2),
            [{'document_label': 'exact', 'text': 'The dog chased the animal', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 17.654017250803907, 'word_infos': [[4, 7, 'overlapping_relation', False, 'Matches DOG directly.'], [8, 14, 'overlapping_relation', False, 'Matches CHASE directly.'], [19, 25, 'overlapping_relation', True, 'Matches ANIMAL directly.']], 'answers': []}, {'document_label': 'specific', 'text': 'I saw a dog. It was chasing a cat', 'text_to_match': 'A dog chases an animal', 'rank': '1=', 'index_within_document': 9, 'subword_index': None, 'start_index': 3, 'end_index': 9, 'sentences_start_index': 0, 'sentences_end_index': 9, 'sentences_character_start_index': 0, 'sentences_character_end_index': 33, 'score': 15.963706826344412, 'word_infos': [[8, 11, 'overlapping_relation', False, 'Matches DOG directly.'], [20, 27, 'overlapping_relation', False, 'Matches CHASE directly.'], [30, 33, 'overlapping_relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}, {'document_label': 'exact-reversed', 'text': 'The animal chased the dog', 'text_to_match': 'A dog chases an animal', 'rank': '3', 'index_within_document': 4, 'subword_index': None, 'start_index': 1, 'end_index': 4, 'sentences_start_index': 0, 'sentences_end_index': 4, 'sentences_character_start_index': 0, 'sentences_character_end_index': 25, 'score': 8.083873269940398, 'word_infos': [[4, 10, 'single', False, 'Matches ANIMAL directly.'], [11, 17, 'relation', False, 'Matches CHASE directly.'], [22, 25, 'relation', True, 'Is a child of ANIMAL in the ontology.']], 'answers': []}] )
        m.close()

    
    def test_multithreading_filtering_with_topic_match_dictionaries(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', number_of_workers=2,
                                          ontology=ontology_for_sm_tests)

        m.parse_and_register_document("The dog chased the cat", 'T11')
        m.parse_and_register_document("The dog chased the cat", 'T12')
        m.parse_and_register_document("The dog chased the cat", 'T21')
        m.parse_and_register_document("The dog chased the cat", 'T22')
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "The dog chased the cat")
        self.assertEqual(len(topic_match_dictionaries), 4)
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T")
        self.assertEqual(len(topic_match_dictionaries), 4)
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T1")
        self.assertEqual(len(topic_match_dictionaries), 2)
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="T22")
        self.assertEqual(len(topic_match_dictionaries), 1)
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "The dog chased the cat", document_label_filter="X")
        self.assertEqual(len(topic_match_dictionaries), 0)
        m.close()

    
    def test_different_match_cutoff_score_high_2(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', number_of_workers=2,
                                          ontology=ontology_for_sm_tests)
        m.parse_and_register_document("A dog then and then and then and then and then a dog")
        topic_match_dictionaries = \
            m.topic_match_documents_against(
                "A dog", different_match_cutoff_score=10000)
        self.assertEqual(len(topic_match_dictionaries), 2)
        m.close()

    
    def test_different_match_cutoff_score_control_2(self):
        ontology_for_sm_tests = holmes.Ontology(os.sep.join((script_directory, 'test_ontology.owl')))
        m = holmes.Manager('en_core_web_sm', number_of_workers=2,
                                          ontology=ontology_for_sm_tests)
        m.parse_and_register_document("A dog then and then and then and then and then a dog")
        topic_match_dictionaries = m.topic_match_documents_against(
                "A dog")
        self.assertEqual(len(topic_match_dictionaries), 1)
        m.close()