Initial: integrated 2025 LawGraph (graphrag_pipeline) + 2026 kg_project

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-17 10:13:39 +08:00
commit 6c1a69af0d
83 changed files with 14295 additions and 0 deletions
@@ -0,0 +1,114 @@
+# 使用示例
+
+## 示例1: 从单个文档提取实体
+
+```python
+from src.preprocessing.document_parser import DocumentParser
+from src.extraction.ner import NERExtractor
+from src.utils.config import load_config
+
+# 加载配置
+config = load_config()
+
+# 解析文档
+parser = DocumentParser()
+doc = parser.parse_docx("../data/1法律/3-中华人民共和国城乡规划法.docx")
+
+# 提取实体
+ner_extractor = NERExtractor(config=config)
+entities = ner_extractor.extract(doc["text"])
+
+print(f"识别到 {sum(len(v) for v in entities.values())} 个实体")
+```
+
+## 示例2: 构建知识图谱
+
+```python
+from src.preprocessing.document_parser import DocumentParser
+from src.kg_builder.indexer import GraphIndexer
+from src.utils.config import load_config
+
+# 加载配置
+config = load_config()
+
+# 解析文档
+parser = DocumentParser()
+docs = parser.parse_directory("../data/1法律")
+
+# 切分为TextUnit
+all_textunits = []
+for doc in docs[:3]:  # 只处理前3个文档
+    textunits = parser.split_into_textunits(doc, max_length=500)
+    all_textunits.extend(textunits)
+
+# 构建知识图谱
+indexer = GraphIndexer(config=config)
+kg = indexer.index(all_textunits)
+
+print(f"图谱包含 {kg.number_of_nodes()} 个节点，{kg.number_of_edges()} 条边")
+```
+
+## 示例3: 查询知识图谱
+
+```python
+from src.kg_builder.graph import KnowledgeGraph
+from src.query.global_search import GlobalSearcher
+from src.query.local_search import LocalSearcher
+
+# 加载图谱
+kg = KnowledgeGraph()
+kg.load("output/kg.json")
+
+# 全局搜索
+global_searcher = GlobalSearcher(kg.graph, communities={})
+result = global_searcher.search("城市更新的法规要求")
+print(result["answer"])
+
+# 局部搜索
+local_searcher = LocalSearcher(kg.graph)
+result = local_searcher.search("城乡规划", depth=2)
+print(f"找到 {result['subgraph']['num_nodes']} 个相关节点")
+```
+
+## 示例4: 法理结构提取
+
+```python
+from src.analysis.legal_structure import LegalStructureExtractor
+
+extractor = LegalStructureExtractor()
+
+# 提取四要素
+text = "为了促进城市可持续发展，应当坚持生态优先、绿色发展原则..."
+elements = extractor.extract_four_elements(text)
+print(elements)
+
+# 提取跨法规引用
+references = extractor.extract_cross_references(text)
+print(references)
+```
+
+## 示例5: 三元组评估
+
+```python
+from src.extraction.evaluator import TripletEvaluator
+
+evaluator = TripletEvaluator()
+
+# 评估多个模型的结果
+peer_groups = {
+    "model_1": [{"head": "A", "relation": "管控", "tail": "B"}],
+    "model_2": [{"head": "A", "relation": "涉及", "tail": "B"}],
+}
+
+result = evaluator.evaluate_peer_groups(
+    peer_groups,
+    source_text="原始文本..."
+)
+
+print(f"最佳模型: {result['best_group']}")
+print(f"评分: {result['scores']}")
+```
+
+
+
+