test

1.py

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+import json
+import csv
+import ast  # Import the ast module
+
+# File paths
+edges_file_path = 'kg2c-2.8.4-edges.jsonl'
+nodes_file_path = 'kg2c-2.8.4-nodes.jsonl'
+output_csv_path = 'output_filtered.csv'
+
+# Load all nodes into a dictionary for quick access by ID
+nodes = {}
+with open(nodes_file_path, 'r') as nodes_file:
+    for line in nodes_file:
+        node_data = json.loads(line)
+        # Get the name or the first alternative name if the primary name is absent
+        name = node_data.get('name') or (node_data.get('all_names')[0] if 'all_names' in node_data and node_data['all_names'] else "Unknown")
+        nodes[node_data['id']] = name
+
+# Process edges that meet the criteria
+with open(edges_file_path, 'r') as edges_file, open(output_csv_path, 'w', newline='', encoding='utf-8') as output_file:
+    csv_writer = csv.writer(output_file)
+    csv_writer.writerow(['ID', 'Fact', 'Source', 'Template', 'Reference', 'Name'])
+
+    for line in edges_file:
+        edge = json.loads(line)
+
+        # Filter based on the knowledge source
+        if edge.get('primary_knowledge_source') == 'infores:semmeddb':
+            publications_info_raw = edge.get('publications_info', '{}')
+            try:
+                # Safely evaluate the string to a Python dictionary
+                publications_info = ast.literal_eval(publications_info_raw)
+            except (SyntaxError, ValueError) as e:
+                # Handle errors in literal evaluation
+                print(f"Error parsing publications_info: {publications_info_raw} with error: {e}")
+                publications_info = {}
+
+            # Extracting the first available sentence from publications_info
+            sentence = next((info.get('sentence', '') for info in publications_info.values()), '')
+
+            # Use names instead of IDs where possible
+            subject_name = nodes.get(edge['subject'], edge['subject'])
+            predicate_name = nodes.get(edge['predicate'], edge['predicate'])
+            object_name = nodes.get(edge['object'], edge['object'])
+
+            # Construct the Fact
+            fact = f"{subject_name} {predicate_name} {object_name}"
+
+            # Write to CSV
+            csv_writer.writerow([edge['id'], fact, sentence, '', '', ''])
+            # print([edge['id'], fact, sentence, '', '', ''])
+
+print("Filtered CSV file has been generated successfully.")

2.py

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+with open('data/RTX-KG2.8.4c_sentence_data.csv', 'r') as fin:
+    data = fin.read().splitlines(True)
+with open('data/RTX-KG2.8.4c_sentence_data.csv', 'w') as fout:
+    fout.writelines(data[1:])
+	#data/RTX-KG2.8.4c_labeled_records.csv
+	#data/RTX-KG2.8.4c_sentence_data.csv
+	#data/RTX-KG2.8.4c_triple_data.csv