| # user_prompt = f"""You are an advanced semantic analyzer. For the given question, perform the following tasks step-by-step: | |
| # 1. **Domain Identification**: | |
| # - Determine the broad subject category (domain) this question belongs to. | |
| # - Examples: film, history, biology, geography, politics, technology, etc (or any other suitable domain) | |
| # 2. **Key Point Extraction**: | |
| # - Identify 2-4 core semantic components that are crucial for answering | |
| # - Include: | |
| # • Key entities (e.g., films, people, locations) | |
| # • Critical attributes (e.g., age, duration, population) | |
| # • Core relationships (e.g., comparison, causality) | |
| # • Measurement dimensions (e.g., time, quantity) | |
| # - Exclude filler words and non-essential descriptors | |
| # **Output Requirements**: | |
| # - Use JSON format: {{"domain": "...", "key_points": [...]}} | |
| # - Keep key_points concise (1-2 words each) | |
| # - Use lowercase for all outputs | |
| # - Separate multiple key_points with commas | |
| # **Examples**: | |
| # Question: "Which film whose director is younger, Charge It To Me or Danger: Diabolik?" | |
| # Output: {{"domain": "film", "key_points": ["director", "age"]}} | |
| # **Now process this question:** | |
| # {{Question}}""" | |
| # print(user_prompt.replace('{Question}', 'Which film whose director is younger, Charge It To Me or Danger: Diabolik?')) | |
| # import json | |
| # txt = "{'domain': 'film', 'key_points': ['directors', 'country', 'same']}" | |
| # print(json.loads(txt)) | |
| # 使用ast.literal_eval解析Python风格字符串（需import ast） | |
| # import ast | |
| # py_style_txt = "{'domain': 'film', 'key_points': ['directors', 'country', 'same']}" | |
| # print(ast.literal_eval(py_style_txt)) # 输出解析后的字典 | |
| import re | |
| def extract_last_braced_content(s): | |
| """ | |
| 提取字符串中被 {} 包裹的内容，如果有多个则返回最后一个。 | |
| :param s: 输入字符串 | |
| :return: 最后一个被 {} 包裹的内容，如果没有则返回 None | |
| """ | |
| # 使用正则表达式匹配所有被 {} 包裹的内容 | |
| # matches = re.findall(r'\{(.*?)\}', s) | |
| matches = re.findall(r'\{.*?\}', s) | |
| # 如果有匹配的内容，返回最后一个；否则返回 None | |
| return matches[-1] if matches else None | |
| # import json | |
| # input_file_path = "/share/project/sunshuang/deep_search/data_syn/data/mixed_data/splits/tagged_domain_keypoints/final_selected_dataset.json" | |
| # with open(input_file_path, 'r') as f: | |
| # data = json.load(f) | |
| # print(len(data)) | |
| text = '{"domain": "development", "key_points": ["human development index", "adopted", "time", "employer"]} \n*Note: The key point "human development index" exceeds the 1-2 word limit. To comply strictly, "hdi" (abbreviation) could be used instead for conciseness, but the original term is more precise. Adjusting for the requirement:* \n{"domain": "development", "key_points": ["hdi", "adopted", "time", "employer"]}' | |
| print(extract_last_braced_content(text)) |