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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)
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