import os import json from collections import defaultdict from transformers import LlamaTokenizer from tqdm import tqdm import argparse def build_entity_triples(triples): entity_triples = defaultdict(list) for triple in triples: subj, relation, obj = triple # 构建完整的三元组字符串 triple_str = f"{subj} - {relation} - {obj}" entity_triples[subj].append(triple_str) return entity_triples def create_paragraphs_with_alignment(subj, old_triples_list, new_triples_list, tokenizer, max_tokens=512): paragraphs_old = [] paragraphs_new = [] boundaries = [] # 记录段落边界的索引 index = 0 start_idx = 0 while index < len(old_triples_list): # 累积令牌长度 candidate_old_triples = old_triples_list[start_idx:index+1] paragraph_text_old = ', '.join(candidate_old_triples) tokens_in_paragraph = len(tokenizer.encode(paragraph_text_old, add_special_tokens=False)) if tokens_in_paragraph > max_tokens: if index == start_idx: # 单个三元组就超出限制,强制添加 boundaries.append(index+1) start_idx = index+1 index += 1 else: boundaries.append(index) start_idx = index else: index += 1 # 添加最后的边界 if start_idx < len(old_triples_list): boundaries.append(len(old_triples_list)) # 根据边界划分段落 start = 0 for end in boundaries: # 旧的段落 old_paragraph_triples = old_triples_list[start:end] paragraph_text_old = ', '.join(old_paragraph_triples) paragraphs_old.append({ "title": subj, "contents": paragraph_text_old }) # 新的段落 new_paragraph_triples = new_triples_list[start:end] paragraph_text_new = ', '.join(new_paragraph_triples) paragraphs_new.append({ "title": subj, "contents": paragraph_text_new }) start = end return paragraphs_old, paragraphs_new def main(args): os.makedirs(os.path.dirname(args.old_output_file), exist_ok=True) os.makedirs(os.path.dirname(args.new_output_file), exist_ok=True) tokenizer = LlamaTokenizer.from_pretrained(args.model_path) with open(args.old_input_json_file, 'r') as f: old_triples = json.load(f) with open(args.new_input_json_file, 'r') as f: new_triples = json.load(f) old_entity_triples = build_entity_triples(old_triples) new_entity_triples = build_entity_triples(new_triples) # 处理所有实体 all_paragraphs_old = [] all_paragraphs_new = [] entities = set(old_entity_triples.keys()).union(new_entity_triples.keys()) for subj in tqdm(entities, desc="Processing entities", unit="entity"): old_triples_list = old_entity_triples.get(subj, []) new_triples_list = new_entity_triples.get(subj, []) # 确保新旧三元组列表长度一致 max_length = max(len(old_triples_list), len(new_triples_list)) if len(old_triples_list) < max_length: old_triples_list.extend([''] * (max_length - len(old_triples_list))) if len(new_triples_list) < max_length: new_triples_list.extend([''] * (max_length - len(new_triples_list))) paragraphs_old, paragraphs_new = create_paragraphs_with_alignment( subj, old_triples_list, new_triples_list, tokenizer, args.max_tokens ) all_paragraphs_old.extend(paragraphs_old) all_paragraphs_new.extend(paragraphs_new) with open(args.old_output_file, 'w') as out_f: json.dump(all_paragraphs_old, out_f, ensure_ascii=False, indent=4) with open(args.new_output_file, 'w') as out_f: json.dump(all_paragraphs_new, out_f, ensure_ascii=False, indent=4) print(f"old {args.old_output_file}") print(f"new {args.new_output_file}") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Process old and new triples") parser.add_argument('--old_input_json_file', type=str, required=True, help='旧的三元组JSON文件的路径。') parser.add_argument('--new_input_json_file', type=str, required=True, help='新的三元组JSON文件的路径。') parser.add_argument('--old_output_file', type=str, required=True, help='保存处理后的旧三元组输出文件的完整路径。') parser.add_argument('--new_output_file', type=str, required=True, help='保存处理后的新三元组输出文件的完整路径。') parser.add_argument('--model_path', type=str, required=True, help='预训练的Tokenizer模型的路径。') parser.add_argument('--max_tokens', type=int, default=512, help='每个段落的最大令牌数。') args = parser.parse_args() main(args)