def create_subgraph_for_person_or_organization(original_tokens: List[str]):
"""
Creates a subgraph (list of concepts and vector of parents) for PERSON or ORGANIZATION
Has as input the original tokens in the sentence
"""
# concepts list
concepts: List[Concept] = []
wiki_literal = '_'.join(original_tokens)
wiki_literal_node = Concept(wiki_literal, wiki_literal)
name_node = Concept('','name')
op_nodes = []
for original_token in original_tokens:
op_nodes.append(Concept(original_token,original_token))
concepts.append(wiki_literal_node)
concepts.append(name_node)
concepts.extend(op_nodes)
# parent vector
vector_of_parents = []
# wiki
vector_of_parents.append([-1])
# name
vector_of_parents.append([-1])
# op literals (have parent name node)
op_literals_parent = [[1] for i in range(len(op_nodes))]
vector_of_parents.extend(op_literals_parent)
return concepts, vector_of_parents
def test_create_from_amr_example_2():
amr_str = """(a / and~e.0
:op2 (p / possible-01~e.8
:ARG1 (a3 / avoid-01~e.10
:ARG0 (h / he~e.7)
:ARG1 (c / censure-01~e.12
:ARG1 h))
:ARG1-of (a2 / actual-02~e.9)
:manner (p2 / promise-01~e.5 :polarity~e.2 -~e.2
:ARG0 h
:mod (a4 / any~e.4))))"""
amr = AMR.parse_string(amr_str)
custom_amr = CustomizedAMR()
custom_amr.create_custom_AMR(amr)
generated_concepts = IdentifiedConcepts()
generated_concepts.create_from_amr('amr_id_2', amr)
expected_concepts = IdentifiedConcepts()
expected_concepts.amr_id = 'amr_id_2'
expected_concepts.ordered_concepts = [
Concept('a', 'and'),
Concept('-', '-', 0),
Concept('a4', 'any'),
Concept('p2', 'promise-01'),
Concept('h', 'he'),
Concept('p', 'possible-01'),
Concept('a2', 'actual-02'),
Concept('a3', 'avoid-01'),
Concept('c', 'censure-01')
]
assert_identified_concepts(expected_concepts, generated_concepts)
def test_create_from_amr_example_reentrancy():
amr_str = """(r / receive-01~e.4
:ARG0 (w / we~e.0)
:ARG1 (t / thing~e.7
:ARG0-of~e.7 (r2 / remind-01~e.7
:ARG1 (p / pay-01~e.6
:ARG0 w)
:ARG2 w))
:ARG2~e.8 (h / hospital~e.10)
:time (n / now~e.2)
:time (a / already~e.3))"""
amr = AMR.parse_string(amr_str)
generated_concepts = IdentifiedConcepts()
generated_concepts.create_from_amr('amr_id_reentrancy', amr)
expected_concepts = IdentifiedConcepts()
expected_concepts.amr_id = 'amr_id_reentrancy'
expected_concepts.ordered_concepts = [
Concept('w', 'we'),
Concept('n', 'now'),
Concept('a', 'already'),
Concept('r', 'receive-01'),
Concept('p', 'pay-01'),
Concept('r2', 'remind-01'),
Concept('t', 'thing'),
Concept('h', 'hospital')
]
assert_identified_concepts(expected_concepts, generated_concepts)
def test_strip_concept_sense():
concept_name = 'recommend-01'
stripped_concept = Concept.strip_concept_sense(concept_name)
expected_concept = 'recommend'
assert stripped_concept == expected_concept
concept_name = 'go'
stripped_concept = Concept.strip_concept_sense(concept_name)
expected_concept = 'go'
assert stripped_concept == expected_concept
concept_name = '-'
stripped_concept = Concept.strip_concept_sense(concept_name)
expected_concept = '-'
assert stripped_concept == expected_concept
def test_create_from_custom_amr_example_1():
amr: AMR = AMR()
amr.node_to_concepts = {'i': 'it', 'v': 'vigorous', 'a': 'advocate-01', 'r': 'recommend-01'}
amr.node_to_tokens = {'i': ['0'], 'v': ['3'], 'a': ['4'], 'r': ['1']}
amr.relation_to_tokens = {'manner': [('2', 'a')]}
amr['i'] = {}
amr['v'] = {}
amr['a'] = {'ARG1': [('i',)], 'manner': [('v',)]}
amr['r'] = {'ARG1': [('a',)]}
generated_concepts = IdentifiedConcepts()
generated_concepts.create_from_amr('amr_id_1', amr)
expected_concepts = IdentifiedConcepts()
expected_concepts.amr_id = 'amr_id_1'
expected_concepts.ordered_concepts = [Concept('i', 'it'), Concept('r', 'recommend-01'), Concept('v', 'vigorous'),
Concept('a', 'advocate-01')]
assert_identified_concepts(expected_concepts, generated_concepts)
def test_generate_dataset_entry():
amr_str = """(r / recommend-01~e.1
:ARG1 (a / advocate-01~e.4
:ARG1 (i / it~e.0)
:manner~e.2 (v / vigorous~e.3)))"""
sentence = """It should be vigorously advocated ."""
generated_entry: ArcsTrainingEntry = generate_dataset_entry('amr_id', amr_str, sentence, 0, 1, False, False)
expected_identified_concepts = IdentifiedConcepts()
expected_identified_concepts.amr_id = 'amr_id'
expected_identified_concepts.ordered_concepts = [Concept('', 'ROOT'),
Concept('i', 'it'),
Concept('r', 'recommend-01'),
Concept('v', 'vigorous'),
Concept('a', 'advocate-01')]
expected_parent_vectors = [(-1, 4, 0, 4, 2)]
assert_identified_concepts(expected_identified_concepts, generated_entry.identified_concepts)
assert_parent_vectors(expected_parent_vectors, generated_entry.parent_vectors)
def test_generate_parent_vector_example_2():
amr_str = """(r / recommend-01~e.1
:ARG1 (a / advocate-01~e.4
:ARG1 (i / it~e.0)
:manner~e.2 (v / vigorous~e.3)))"""
amr: AMR = AMR.parse_string(amr_str)
identified_concepts = IdentifiedConcepts()
identified_concepts.ordered_concepts = [
Concept('', 'ROOT'),
Concept('i', 'it'),
Concept('r', 'recommend-01'),
Concept('v', 'vigorous'),
Concept('a', 'advocate-01')
]
generated_parent_vector = generate_parent_vectors(amr, identified_concepts)
expected_parent_vector = [[-1, 4, 0, 4, 2]]
assert_parent_vectors(expected_parent_vector, generated_parent_vector)
def test_create_from_amr_example_1():
amr_str = """(r / recommend-01~e.1
:ARG1 (a / advocate-01~e.4
:ARG1 (i / it~e.0)
:manner~e.2 (v / vigorous~e.3)))"""
amr = AMR.parse_string(amr_str)
generated_concepts = IdentifiedConcepts()
generated_concepts.create_from_amr('amr_id_1', amr)
expected_concepts = IdentifiedConcepts()
expected_concepts.amr_id = 'amr_id_1'
expected_concepts.ordered_concepts = [
Concept('i', 'it'),
Concept('r', 'recommend-01'),
Concept('v', 'vigorous'),
Concept('a', 'advocate-01')
]
assert_identified_concepts(expected_concepts, generated_concepts)
def test_generate_parent_vector():
amr: AMR = AMR()
amr.roots = ['r']
amr.reentrance_triples = []
amr.node_to_concepts = {'i': 'it', 'v': 'vigorous', 'a': 'advocate-01', 'r': 'recommend-01'}
amr.node_to_tokens = {'i': ['0'], 'v': ['3'], 'a': ['4'], 'r': ['1']}
amr.relation_to_tokens = {'manner': [('2', 'a')]}
amr['i'] = {}
amr['v'] = {}
amr['a'] = {'ARG1': [('i',)], 'manner': [('v',)]}
amr['r'] = {'ARG1': [('a',)]}
identified_concepts = IdentifiedConcepts()
identified_concepts.ordered_concepts = [Concept('', 'ROOT'),
Concept('i', 'it'),
Concept('r', 'recommend-01'),
Concept('v', 'vigorous'),
Concept('a', 'advocate-01')]
generated_parent_vector = generate_parent_vectors(amr, identified_concepts, 1)
expected_parent_vector = [(-1, 4, 0, 4, 2)]
assert_parent_vectors(expected_parent_vector, generated_parent_vector)
def test_generate_amr_node_for_vector_of_parents():
identified_concepts: IdentifiedConcepts = IdentifiedConcepts()
identified_concepts.ordered_concepts = [Concept('', 'ROOT'), # 0
Concept('i', 'it'), # 1
Concept('r', 'recommend-01'), # 2
Concept('v', 'vigorous'), # 3
Concept('a', 'advocate-01') # 4
]
predicted_vector_of_parents = [[-1], [4], [0], [4], [2]]
relations_dict = {
('recommend-01', 'advocate-01'): 'ARG1',
('advocate-01', 'it'): 'ARG1',
('advocate-01', 'vigorous'): 'manner'
}
amr: Node = generate_amr_node_for_vector_of_parents(identified_concepts,
predicted_vector_of_parents,
relations_dict)
generated_amr_str = amr.amr_print_with_reentrancy()
gold_amr_str = """(r / recommend-01~e.1
:ARG1 (a / advocate-01~e.4
:ARG1 (i / it~e.0)
:manner~e.2 (v / vigorous~e.3)))"""
smatch = calculate_smatch(generated_amr_str, gold_amr_str)
assert smatch == 1
def test_post_processing_on_parent_vector():
sentence = 'Comrade PERSON once said that the Communist Party will not be overthrown - ' \
'if it falls , it will be brought down from within the party itself .'
metadata = {1: ['Deng', 'Xiaoping']}
identified_concepts = IdentifiedConcepts()
identified_concepts.ordered_concepts = [Concept('', 'ROOT'), Concept('c', 'comrade'),
Concept('h', 'have-org-role-91'),
Concept('p', 'PERSON'), Concept('o', 'once'), Concept('s', 'say-01'),
Concept('p2', 'political-party'),
Concept('Communist_Party_of_China', 'Communist_Party_of_China'),
Concept('n2', 'name'),
Concept('Communist', 'Communist'), Concept('Party', 'Party'),
Concept('-', '-'), Concept('o', 'overthrow-01'),
Concept('a', 'and'), Concept('f', 'fall-05'), Concept('b', 'bring-down'),
Concept('p3', 'person'), Concept('h2', 'have-org-role-91')
]
vector_of_parents = [[-1], [2], [3],
[5], [5], [0],
[12, 14, 15, 16, 17],
[6], [6],
[8], [8],
[12], [13],
[5], [15], [13],
[15], [16]]
post_processing_on_parent_vector(identified_concepts, vector_of_parents, sentence, metadata)
expected_ordered_concepts = [Concept('', 'ROOT'), Concept('c', 'comrade'),
Concept('h', 'have-org-role-91'),
Concept('p', 'person'), Concept('o', 'once'), Concept('s', 'say-01'),
Concept('p2', 'political-party'),
Concept('Communist_Party_of_China', 'Communist_Party_of_China'),
Concept('n2', 'name'),
Concept('Communist', 'Communist'), Concept('Party', 'Party'),
Concept('-', '-'), Concept('o', 'overthrow-01'),
Concept('a', 'and'), Concept('f', 'fall-05'), Concept('b', 'bring-down'),
Concept('p3', 'person'), Concept('h2', 'have-org-role-91'),
Concept('Deng_Xiaoping', 'Deng_Xiaoping'), Concept('', 'name'),
Concept('Deng', 'Deng'), Concept('Xiaoping', 'Xiaoping')
]
expected_vector_of_parents = [[-1], [2], [3],
[5], [5], [0],
[12, 14, 15, 16, 17],
[6], [6],
[8], [8],
[12], [13],
[5], [15], [13],
[15], [16],
[3], [3],
[19], [19]]
assert identified_concepts.ordered_concepts == expected_ordered_concepts
assert vector_of_parents == expected_vector_of_parents
def test_generate_parent_vector_example_2():
amr_str = """(m / man~e.2
:ARG1-of (m2 / marry-01~e.1)
:ARG0-of (l / love-01~e.9
:ARG1~e.10 (y / you~e.11)
:ARG1-of (r / real-04~e.6)
:condition-of~e.4 (a3 / and~e.16
:op1 (g / go-06~e.14
:ARG2 (a / ahead~e.15)
:mod (j / just~e.13))
:op2 (o2 / or~e.22
:op1 (f / file-01~e.17
:ARG4~e.18 (d / divorce-01~e.19)
:time (n / now~e.20))
:op2 (m3 / move-01~e.25
:ARG2 (o / out-06~e.26
:ARG2~e.27 (h / house~e.29
:poss~e.28 m~e.28))
:time n~e.30
:mod (a2 / at-least~e.23,24))))))"""
amr: AMR = AMR.parse_string(amr_str)
identified_concepts = IdentifiedConcepts()
identified_concepts.ordered_concepts = [
Concept('', 'ROOT'), # 0
Concept('m2', 'marry-01'), # 1
Concept('m', 'man'), # 2
Concept('r', 'real-04'), # 3
Concept('l', 'love-01'), # 4
Concept('y', 'you'), # 5
Concept('j', 'just'), # 6
Concept('g', 'go-06'), # 7
Concept('a', 'ahead'), # 8
Concept('a3', 'and'), # 9
Concept('f', 'file-01'), # 10
Concept('d', 'divorce-01'), # 11
Concept('n', 'now'), # 12
Concept('o2', 'or'), # 13
Concept('a2', 'at-least'), # 14
Concept('m3', 'move-01'), # 15
Concept('o', 'out-06'), # 16
Concept('h', 'house') # 17
]
generated_parent_vector = generate_parent_vectors(amr, identified_concepts,
2)
expected_parent_vector = [
(-1, 2, 0, 4, 2, 4, 7, 9, 7, 4, 13, 10, 10, 9, 15, 13, 15, 16),
(-1, 2, 0, 4, 2, 4, 7, 9, 7, 4, 13, 10, 15, 9, 15, 13, 15, 16)
]
assert_parent_vectors(expected_parent_vector, generated_parent_vector)
def test__create_from_amr_with_2_polarites():
amr_str = """(a / and~e.0
:op2 (p2 / practice-01~e.13
:ARG1 (l / loan-01~e.12
:ARG2 (p / person~e.11
:ARG0-of~e.11 (s / study-01~e.11)))
:mod (s2 / sane~e.10 :polarity~e.10 -~e.10)
:ARG1-of (i2 / identical-01~e.16
:ARG2~e.19 (p3 / practice-01~e.24
:ARG1 (l2 / loan-01~e.23
:ARG1 (m / mortgage-01~e.22))
:mod (s3 / sane~e.21 :polarity~e.21 -~e.21))
:manner (w / way~e.18
:mod (e / every~e.18)))
:ARG0-of (c2 / cause-01~e.3,8
:ARG1 (b / be-located-at-91~e.5,7
:ARG1 (t / they~e.4)
:ARG2 (t2 / there~e.6))
:mod (o / only~e.2))))"""
amr: AMR = AMR.parse_string(amr_str)
generated_concepts = IdentifiedConcepts()
generated_concepts.create_from_amr('amr_2_polarities', amr)
expected_concepts = IdentifiedConcepts()
expected_concepts.amr_id = 'amr_2_polarities'
expected_concepts.ordered_concepts = [
Concept('a', 'and'),
Concept('o', 'only'),
Concept('c2', 'cause-01'),
Concept('t', 'they'),
Concept('b', 'be-located-at-91'),
Concept('t2', 'there'),
Concept('-', '-', 0),
Concept('s2', 'sane'),
Concept('s', 'study-01'),
Concept('p', 'person'),
Concept('l', 'loan-01'),
Concept('p2', 'practice-01'),
Concept('i2', 'identical-01'),
Concept('e', 'every'),
Concept('w', 'way'),
Concept('-', '-', 1),
Concept('s3', 'sane'),
Concept('m', 'mortgage-01'),
Concept('l2', 'loan-01'),
Concept('p3', 'practice-01')
]
assert_identified_concepts(expected_concepts, generated_concepts)