New AMR Rule: transduction.property_class_classifier

tenet/scheme/amr_clara_rule/__init__.py

@@ -14,6 +14,7 @@ from scheme.amr_clara_rule.transduction.composite_class_extractor_1 import *
 from scheme.amr_clara_rule.transduction.composite_class_extractor_2 import * 
 
 from scheme.amr_clara_rule.transduction.phenomena_modality_classifier import * 
+from scheme.amr_clara_rule.transduction.property_class_classifier import * 
 
 from scheme.amr_clara_rule.transduction.phenomena_polarity_analyzer_1 import * 
 from scheme.amr_clara_rule.transduction.phenomena_polarity_analyzer_2 import * 

tenet/scheme/amr_clara_rule/transduction/atom_class_extractor.py

@@ -140,12 +140,8 @@ def extract_atom_class(graph):
     rule_triple_list = []
     for pattern in pattern_set:
         
-        # -- New Net Construction (from 3 nets)
-        new_class, triple_list = __construct_atom_class_net(
-            graph, pattern.leaf, pattern.conceptName)
-            
-        # -- Resulting List Update
-        # class_net_list.append(new_class)
+        # -- New Net Construction
+        new_class, triple_list = __construct_atom_class_net(graph, pattern.leaf, pattern.conceptName)
         rule_triple_list += triple_list
             
     return rule_label, rule_triple_list
\ No newline at end of file

tenet/scheme/amr_clara_rule/transduction/property_class_classifier.py

+#!/usr/bin/python3.10
+# -*-coding:Utf-8 -*
+
+#==============================================================================
+# TENET: Rule to modality phenomena classification
+#------------------------------------------------------------------------------
+# AMR rule to classify modality phenomena
+# Rule: modality_phenomena classification
+#==============================================================================
+
+from rdflib import Graph
+
+import transduction
+from transduction import net
+from transduction.query_builder import generate_select_query
+from transduction.rdfterm_computer import produce_uriref, produce_literal
+
+
+#==============================================================================
+# Pattern Search: modality_phenomena
+#==============================================================================
+
+def __search_pattern(graph):
+    query_code = ''
+    result_set = []
+    for arg_relation in ['amr:role_ARG0', 'amr:role_ARG1', 'amr:role_ARG2']:
+        select_data_list = ['?property_net']
+        clause_list = [f'?left_property_net a [rdfs:subClassOf* net:Property_Net].',
+                       f'?property_net a [rdfs:subClassOf* net:Atom_Property_Net].',
+                       f'?left_property_net {arg_relation} ?property_net.']
+        query_code = generate_select_query(graph, select_data_list, clause_list)
+        result_set += graph.query(query_code)
+    return query_code, result_set
+
+
+
+#==============================================================================
+# Useful Computation Method(s)
+#==============================================================================  
+
+def __propagate_relation(target_net, base_net):
+    target_net.input_relation_list = base_net.input_relation_list
+    target_net.output_relation_list = base_net.output_relation_list 
+    
+    
+#==============================================================================
+# Construct Method(s)
+#==============================================================================
+
+def __construct_atom_class_net(graph, property_net):
+
+    # -- Net Composition
+    atom_class_net = net.AtomClassNet(graph)
+    atom_class_net.compose(property_net)
+    
+    # -- Data Computation
+    atom_class_net.class_name = property_net.naming
+
+    # -- Net Naming
+    atom_class_net.naming = property_net.naming
+    
+    # -- Relation Propagation
+    __propagate_relation(atom_class_net, property_net) 
+    
+    # -- Finalization
+    atom_class_net.finalize()
+    triple_definition = atom_class_net.generate_triple_definition()
+    
+    return atom_class_net, triple_definition
+  
+    
+#==============================================================================
+# Main Method
+#==============================================================================
+
+def reclassify_argument_property_to_class(graph):
+    
+    # -- Rule Initialization 
+    rule_label = 'reclassify argument property to class' 
+    rule_triple_list = []
+    
+    # -- Search for patterns 
+    _, pattern_set = __search_pattern(graph)
+    
+    # -- Pattern Analysis
+    for pattern in pattern_set:
+        atom_property_net = net.AtomPropertyNet(graph, uri=pattern.property_net)
+        _, triple_list = __construct_atom_class_net(graph, atom_property_net)
+        rule_triple_list += triple_list
+        rule_triple_list += atom_property_net.deprecate()
+    
+    return rule_label, rule_triple_list
\ No newline at end of file

tenet/scheme/amr_scheme_clara_1.py

@@ -104,74 +104,6 @@ amr_reification_sequence = {
 # # Transduction Sequences
 # # ---------------------------------------------
 
-phenomena_application_and_sequence = {
-    'label': 'phenomena-application-and-sequence',
-    'comment': 'Application of phenomena',
-    'rule_key_list': ['and-conjunction-phenomena-application-1',
-                      'and-conjunction-phenomena-application-2',
-                      'and-conjunction-phenomena-application-3',
-                      'and-conjunction-phenomena-application-4',
-                      'and-conjunction-phenomena-application-5',
-                      'and-conjunction-phenomena-application-6'
-                      ]
-    }
-
-
-composite_property_extraction_sequence = {
-    'label': 'composite-property-extraction-sequence',
-    'comment': 'creation of composite properties from properties',
-    'rule_key_list': ['create-composite-property-net-from-property-1',
-                      'create-composite-property-net-from-property-2']
-    }
-
-
-restriction_adding_sequence = {
-    'label': 'restriction-adding-sequence',
-    'comment': 'add restriction to class from property',
-    'rule_key_list': ['add-restriction-to-class-net-from-property-1']
-    }
-
-
-phenomena_checking_sequence = {
-    'label': 'phenomena-checking-sequence',
-    'comment': 'creation of phenomena nets',
-    'rule_key_list': ['expand-and-or-conjunction-phenomena-net',
-                      'expand-degree-phenomena-net-1',
-                      'expand-degree-phenomena-net-2',
-                      'expand-degree-phenomena-net-3',
-                      'expand-degree-phenomena-net-4',
-                      'expand-degree-phenomena-net-5',
-                      'expand-degree-phenomena-net-6']
-    }
-
-
-composite_class_extraction_sequence_2 = {
-    'label': 'composite-class-extraction-sequence-2',
-    'comment': 'creation of composite classes from phenomena',
-    'rule_key_list': ['create-composite-class-net-from-phenomena-1',
-                      'create-composite-class-net-from-phenomena-2',
-                      'create-composite-class-net-from-phenomena-3',
-                      'create-composite-class-net-from-phenomena-4']
-    }
-
-
-classification_sequence = {
-    'label': 'classification-sequence',
-    'comment': 'net classification',
-    'rule_key_list': ['classify-net-from-core-1',
-                      'classify-net-from-core-2',
-                      'classify-net-from-core-3',
-                      # -- old --- 'classify-net-from-mod',
-                      'classify-net-from-part',
-                      'classify-net-from-domain',
-                      'classify-net-from-degree-phenomena-1',
-                      'classify-net-from-degree-phenomena-2',
-                      'classify-net-from-degree-phenomena-3',
-                      'propagate-individual-1',
-                      'propagate-individual-2',
-                      'reclassify-deprecated-net']
-    }
-
 atomic_extraction_sequence = ['atomic extraction sequence',
                               rule.extract_atom_class,
                               rule.extract_atom_individual,
@@ -181,11 +113,12 @@ atomic_extraction_sequence = ['atomic extraction sequence',
                               rule.propagate_atom_relation
                               ]
 
-phenomena_analyze_sequence_1 = ['phenomena analyze sequence (1)',
-                                rule.classify_modality_phenomena
+classification_sequence_1 = ['classification sequence (1)',
+                             rule.classify_modality_phenomena,
+                             rule.reclassify_argument_property_to_class
                              ]
 
-phenomena_analyze_sequence_2 = ['phenomena analyze sequence (2)',
+phenomena_analyze_sequence_1 = ['phenomena analyze sequence (1)',
                                 rule.analyze_phenomena_polarity_1,
                                 rule.analyze_phenomena_polarity_2,
                                 rule.analyze_phenomena_polarity_3,
@@ -195,7 +128,7 @@ phenomena_analyze_sequence_2 = ['phenomena analyze sequence (2)',
                                 rule.classify_modality_phenomena
                                 ]
 
-phenomena_analyze_sequence_3 = ['phenomena analyze sequence (3)',
+phenomena_analyze_sequence_2 = ['phenomena analyze sequence (2)',
                                 rule.analyze_phenomena_or_1,
                                 rule.analyze_phenomena_or_2,
                                 rule.analyze_phenomena_and_1,
@@ -235,9 +168,9 @@ scheme = {
     
     'transduction': [transduction_refinement_sequence,
                      atomic_extraction_sequence,
+                      classification_sequence_1,
                       phenomena_analyze_sequence_1,
                       phenomena_analyze_sequence_2,
-                       phenomena_analyze_sequence_3,
                       composite_property_extraction_sequence,
                       composite_class_extraction_sequence,
                       odrl_extraction_sequence

tests/dev_tests/test_rule_phenomena_polarity.py → tests/dev_tests/test_rule_classifier.py

@@ -16,10 +16,12 @@ FILE_PATH = f'{os.path.dirname(os.path.abspath(__file__))}'
 INPUT_DIR_PATH = f'{FILE_PATH}/test_data/'
 OUTPUT_DIR_PATH = f'{FILE_PATH}/test_data/'
 
-TEST_FILE_NAME_1 = 'modality-devGraph-1'
+TEST_FILE_NAME_1 = 'classifier-devGraph-1'
+TEST_FILE_NAME_2 = 'classifier-devGraph-2'
 
 from context import tenet
 from tenet.scheme.amr_clara_rule.transduction import phenomena_modality_classifier as rule_1
+from tenet.scheme.amr_clara_rule.transduction import property_class_classifier as rule_2
 from tenet.scheme import amr_master_rule as rule
 from tenet.scheme import amr_clara_rule
 
@@ -90,7 +92,7 @@ def add_triples_in_graph(test_file_name, graph, triple_list):
 # Development Test
 #==============================================================================
         
-def test_search_pattern(graph):    
+def test_search_pattern_1(graph):    
     query_code, pattern_set = rule_1.__search_pattern(graph)
     print(f'\n ----- query code: {query_code}')
     print(f'\n ----- number of selection found: {len(pattern_set)}')
@@ -101,6 +103,17 @@ def test_search_pattern(graph):
     return pattern_set
 
         
+def test_search_pattern_2(graph):    
+    query_code, pattern_set = rule_2.__search_pattern(graph)
+    print(f'\n ----- query code: {query_code}')
+    print(f'\n ----- number of selection found: {len(pattern_set)}')
+    for selection in pattern_set: 
+        result_str = f'>>> '
+        result_str += f'{selection.property_net.n3(graph.namespace_manager)}'
+        print(result_str)        
+    return pattern_set
+    
+
 #==============================================================================
 # Unit Test
 #==============================================================================
@@ -123,20 +136,34 @@ if __name__ == '__main__':
       
     print('\n *** Test Preparation ***')
     graph_1 = load_test_graph(TEST_FILE_NAME_1)
+    graph_2 = load_test_graph(TEST_FILE_NAME_2)
     print('\n \n')
     
     
-    print('\n ///////////////////// Extraction Rule 1')
+    print('\n ///////////////////// Classifier Rule 1')
     
     print('\n *** Step Test ***')
     
     print('\n -- Step 1: Search Pattern')
-    pattern_set = test_search_pattern(graph_1)
-        
+    pattern_set = test_search_pattern_1(graph_1)    
     print('\n \n')
     
     print('\n *** Unit Test ***')
     test_rule_application(TEST_FILE_NAME_1, graph_1, amr_clara_rule.classify_modality_phenomena)
     print('\n \n')
     
+    
+    print('\n ///////////////////// Classifier Rule 2')
+    
+    print('\n *** Step Test ***')
+    
+    print('\n -- Step 1: Search Pattern')
+    pattern_set = test_search_pattern_2(graph_1)   
+    pattern_set = test_search_pattern_2(graph_2)    
+    print('\n \n')
+    
+    print('\n *** Unit Test ***')
+    test_rule_application(TEST_FILE_NAME_2, graph_2, amr_clara_rule.reclassify_argument_property_to_class)
+    print('\n \n')
+
     print('\n *** - ***')
\ No newline at end of file

tests/dev_tests/test_rule_phenomena_classifier.py

-#!/usr/bin/python3.10
-# -*-coding:Utf-8 -*
-
-#==============================================================================
-# TENET: Extraction Rule Test
-#------------------------------------------------------------------------------
-# Script to test rules under development
-#==============================================================================
-
-import subprocess, os
-from rdflib import Graph, Namespace
-from rdflib.namespace import NamespaceManager, FOAF, RDF
-from rdflib import URIRef, Literal, BNode
-
-FILE_PATH = f'{os.path.dirname(os.path.abspath(__file__))}'
-INPUT_DIR_PATH = f'{FILE_PATH}/test_data/'
-OUTPUT_DIR_PATH = f'{FILE_PATH}/test_data/'
-
-TEST_FILE_NAME_1 = 'mod-analyzer-devGraph-1'
-TEST_FILE_NAME_2 = 'mod-analyzer-devGraph-2'
-
-from context import tenet
-from tenet.transduction.rdfterm_computer import __update_uri_with_prefix
-from tenet.transduction import rdfterm_computer, prefix_handle
-from tenet.transduction import net
-from tenet.scheme.amr_rule.transduction import phenomena_mod_analyzer_1 as rule_1
-from tenet.scheme import amr_rule
-
-
-
-#==============================================================================
-# Useful Methods
-#==============================================================================
-
-def load_test_graph(test_file_name):
-    print(f'\n -- Test Graph Loading')
-    graph = Graph()
-    prefix_handle.update_graph_namespacemanager(graph)
-    graph_path = f'{INPUT_DIR_PATH}{test_file_name}.ttl'
-    graph.parse(graph_path)
-    print(f" ----- Graph Loaded ({len(graph)})")
-    return graph
-
-
-def define_clause_list(composition_pattern_list):
-    clause_list = []
-    for (net_1, relation, net_2) in composition_pattern_list:
-        clause_list.append(f'{net_1} {relation} {net_2}.')
-    return clause_list
-
-
-def print_triple(graph, triple, num=-1):
-    num_str = f'[{num}]' if num > -1 else '[-]'
-    (s, p, o) = triple
-    s = __update_uri_with_prefix(graph, s)
-    p = __update_uri_with_prefix(graph, p)
-    o = __update_uri_with_prefix(graph, o)
-    print(f' {num_str} {s} {p} {o}')
-    
-
-def add_triples_in_graph(test_file_name, graph, triple_list):
-    print(f'\n -- Adding triple(s) in graph')       
-    print(f" ----- Graph length before update: {len(graph)}")
-    print(f" ----- Number of triples to add: {len(triple_list)}")
-    
-    print(f" ----- Added triples:")
-    n = 0
-    for triple in triple_list:
-        n += 1
-        print_triple(graph, triple, num=n)
-        graph.add(triple)      
-        
-    print(f" ----- Graph length after update: {len(graph)}")
-    
-    output_graph_path = f'{OUTPUT_DIR_PATH}{test_file_name}.result.ttl'
-    output_graph_uri = f'https://amr.tetras-libre.fr/rdf/{test_file_name}/result'
-    print(f'\n -- Serialize test graph to {output_graph_path}')
-    graph.serialize(destination=output_graph_path, 
-                    format='turtle',
-                    base=output_graph_uri)
-
-
-
-#==============================================================================
-# Development / Step Test
-#==============================================================================
-        
-def test_search_pattern_1(graph):
-    
-    print('\n -- Step 1: Search Pattern')
-    _, pattern_set = rule_1.__search_pattern(graph)
-    print(f'\n ----- number of selection found: {len(pattern_set)}')
-    for row in pattern_set: 
-        result_str = f'>>> '
-        result_str += f' {row.class_net_1.n3(graph.namespace_manager)}'
-        result_str += f' {row.class_net_2.n3(graph.namespace_manager)}'
-        print(result_str) 
-        
-    print('\n -- Step 2: Disjoint Cover Verification')
-    result_set = []
-    
-    return pattern_set
-        
-    
-
-#==============================================================================
-# Unit Test
-#==============================================================================
-
-def test_rule_application(test_file_name, graph, rule):    
-    print('\n -- Rule Test')
-    
-    rule_label, new_triple_list = rule(graph)
-    print(f' ----- label: {rule_label}')
-    print(f' ----- new_triple_list ({len(new_triple_list)}):')
-    
-    add_triples_in_graph(test_file_name, graph, new_triple_list)
-    
-
-
-#==============================================================================
-# Test Script
-#==============================================================================
-
-if __name__ == '__main__':
-      
-    print('\n *** Test Preparation ***')
-    graph_1 = load_test_graph(TEST_FILE_NAME_1)
-    print('\n \n')
-    
-    print('\n ///////////////////// Extraction Rule 1')
-    
-    print('\n *** Step Test ***')
-    pattern_set = test_search_pattern_1(graph_1)
-    print('\n \n')
-    
-    print('\n *** Unit Test ***')
-    test_rule_application(TEST_FILE_NAME_1, graph_1, rule_1.analyze_phenomena_mod_1)
-    print('\n \n')
-
-    print('\n *** - ***')
\ No newline at end of file

tests/input/amrDocuments/dev/asail_odrl_sentences/s14.stog.amr.ttl

+@prefix ns1: <http://amr.isi.edu/frames/ld/v1.2.2/> .
+@prefix ns2: <http://amr.isi.edu/rdf/core-amr#> .
+@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
+
+ns2:Concept a rdfs:Class ;
+    rdfs:label "AMR-Concept" .
+
+ns2:Role a rdfs:Class ;
+    rdfs:label "AMR-Role" .
+
+<http://amr.isi.edu/amr_data/asail_odrl_sentences-14#root01> a ns2:AMR ;
+    ns2:has-id "asail_odrl_sentences-14" ;
+    ns2:has-sentence "You may distribute the Work." ;
+    ns2:root <http://amr.isi.edu/amr_data/asail_odrl_sentences-14#p> .
+
+ns1:distribute-01.ARG0 a ns1:FrameRole .
+
+ns1:distribute-01.ARG1 a ns1:FrameRole .
+
+ns1:permit-01.ARG1 a ns1:FrameRole .
+
+ns2:NamedEntity a ns2:Concept ;
+    rdfs:label "AMR-EntityType",
+        "AMR-Term" .
+
+<http://amr.isi.edu/amr_data/asail_odrl_sentences-14#d> a ns1:distribute-01 ;
+    ns1:distribute-01.ARG0 <http://amr.isi.edu/amr_data/asail_odrl_sentences-14#y> ;
+    ns1:distribute-01.ARG1 <http://amr.isi.edu/amr_data/asail_odrl_sentences-14#w> .
+
+<http://amr.isi.edu/amr_data/asail_odrl_sentences-14#p> a ns1:permit-01 ;
+    ns1:permit-01.ARG1 <http://amr.isi.edu/amr_data/asail_odrl_sentences-14#d> .
+
+<http://amr.isi.edu/amr_data/asail_odrl_sentences-14#w> a ns1:work-01 .
+
+<http://amr.isi.edu/amr_data/asail_odrl_sentences-14#y> a <http://amr.isi.edu/rdf/amr-terms#you> .
+
+ns1:distribute-01 a ns2:Frame .
+
+ns1:permit-01 a ns2:Frame .
+
+ns1:work-01 a ns2:Frame .
+
+<http://amr.isi.edu/rdf/amr-terms#you> a ns2:Concept .
+
+ns1:FrameRole a ns2:Role ;
+    rdfs:label "AMR-PropBank-Role" .
+
+ns2:Frame a ns2:Concept ;
+    rdfs:label "AMR-PropBank-Frame" .
+

tests/test_tenet_clara_main.py

@@ -29,7 +29,7 @@ from context import tenet
 # -- Input Data
 test_data_dir = f'{INPUT_DIR_PATH}amrDocuments/'
 
-uuid_num = '12'
+uuid_num = '13'
 amrld_dir_path = f'{test_data_dir}dev/asail_odrl_sentences/'
 amrld_file_path = f'{amrld_dir_path}s{uuid_num}.stog.amr.ttl'
 base_output_name = f'aos{uuid_num}'
@@ -51,18 +51,18 @@ technical_dir_path = f'{out_dir_path}technical-data/'
 
 os.chdir('..')
 # -- Extraction from a file
-# factoids = tenet.create_ontology_from_amrld_file(amrld_file_path, 
-#                                                   onto_prefix=onto_prefix,
-#                                                   out_file_path=out_file_path,
-#                                                   technical_dir_path=technical_dir_path)
-
-
-# -- Extraction from a directory (all files in a directory)
-factoids = tenet.create_ontology_from_amrld_dir(amrld_dir_path, 
+factoids = tenet.create_ontology_from_amrld_file(amrld_file_path, 
                                                   onto_prefix=onto_prefix,
                                                   out_file_path=out_file_path,
                                                   technical_dir_path=technical_dir_path)
 
+
+# -- Extraction from a directory (all files in a directory)
+# factoids = tenet.create_ontology_from_amrld_dir(amrld_dir_path, 
+#                                                 onto_prefix=onto_prefix,
+#                                                 out_file_path=out_file_path,
+#                                                 technical_dir_path=technical_dir_path)
+
 print(factoids)