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
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+#!/usr/bin/env python
+"""
+知识抽取脚本
+示例用法：python scripts/extract.py --input data/sample.txt --output output/entities.json
+"""
+
+import argparse
+import json
+import logging
+import sys
+from pathlib import Path
+
+# 添加src到路径
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from src.preprocessing.document_parser import DocumentParser
+from src.extraction.ner import NERExtractor
+from src.utils.config import Config, load_config
+
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="法规知识抽取工具")
+    parser.add_argument(
+        "--input",
+        type=str,
+        required=True,
+        help="输入文件路径（.docx或.txt）"
+    )
+    parser.add_argument(
+        "--output",
+        type=str,
+        default="output/entities.json",
+        help="输出文件路径"
+    )
+    parser.add_argument(
+        "--use-verification",
+        action="store_true",
+        default=True,
+        help="使用二次对话验证"
+    )
+    
+    args = parser.parse_args()
+    
+    # 加载配置
+    config = load_config()
+    
+    # 确保输出目录存在
+    output_path = Path(args.output)
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    
+    # 解析文档
+    input_path = Path(args.input)
+    if input_path.suffix == ".docx":
+        parser = DocumentParser()
+        doc_data = parser.parse_docx(str(input_path))
+        text = doc_data["text"]
+    else:
+        # 假设是纯文本文件
+        with open(input_path, "r", encoding="utf-8") as f:
+            text = f.read()
+    
+    # 执行NER
+    logger.info("开始实体识别...")
+    ner_extractor = NERExtractor(config=config)
+    entities = ner_extractor.extract(text, use_verification=args.use_verification)
+    
+    # 保存结果
+    result = {
+        "input_file": str(input_path),
+        "entities": entities,
+        "statistics": {
+            entity_type: len(entity_list)
+            for entity_type, entity_list in entities.items()
+        }
+    }
+    
+    with open(output_path, "w", encoding="utf-8") as f:
+        json.dump(result, f, ensure_ascii=False, indent=2)
+    
+    logger.info(f"实体识别完成，结果已保存到: {output_path}")
+    logger.info(f"统计信息: {result['statistics']}")
+
+
+if __name__ == "__main__":
+    main()
+
+
+
+
+