time_string_format_zh: |
  {year}年{month}{day}日{weekday}{hour}点


time_string_format: |
  {month} {day}, {year}, {weekday}, at {hour}


get_observation_with_time_system_zh: |
  任务：从下面的{num_obs}句{user_name}句子中依次提取出关于{user_name}的重要信息，相应的关键词与时间信息。如果没有重要信息则回答“无”，最多提取{num_obs}条信息。
  每一句{user_name}句子的格式是：<序号> <对话时间> {user_name}：<句子>
  {user_name}的重要信息可以包含用户基本信息，用户画像信息，用户兴趣偏好信息，用户性格，用户价值观，用户人际关系，用户重大事件转折点等等重要信息。
  如果句子中只包含{user_name}假设的信息或者{user_name}虚构的内容比如{user_name}创作的小说或剧本，回答“无”。
  如果{user_name}信息涉及时间，则结合对话时间推断{user_name}信息的时间信息，没有则不输出。
  对每个句子都做一次信息提取，最后一共输出{num_obs}条信息。
  请一步步思考，并一定要按如下格式依次输出，最后的结果一定要加<>:
  思考：思考的依据和过程，50字以内。
  信息：<句子序号> <时间信息或不输出> <明确的重要信息或“无”> <关键词>


get_observation_with_time_system: |
  Task: Extract important information about {user_name} from the following {num_obs} sentences of {user_name}, including relevant keywords and time information. If there is no important information, answer "none", with a maximum of {num_obs} pieces of information extracted.
  Each sentence from {user_name} is formatted as follows: <serial number> <conversation time> {user_name}: <sentence>.
  Important information about {user_name} can include basic information, user profile information, interest preferences, personality, values, human relationships, significant life events, etc.
  If a sentence only contains hypothetical information or fictional content created by {user_name} (e.g., novels or scripts), answer "none".
  If {user_name}'s information involves time, infer the time information based on the conversation time; if not, do not output.
  Analyze each sentence once to extract information and output a total of {num_obs} pieces of information.
  Please think step-by-step and be sure to output in the following format, with the final results enclosed in <>:
  Thought: Basis and process of thought, within 50 words.
  Information: <Sentence Number> <Time information or do not output> <Clear important information or "None"> <Keywords>


get_observation_with_time_few_shot_zh: |
  示例1：
  {user_name}句子：
  1 2022年5月1日周二3点 {user_name}：帮我写一段给同事张三女儿三岁生日的祝福语。
  2 2022年5月2日周二17点 {user_name}：公元1400年至1550年中国历史大事表。
  3 2022年5月3日周二18点 {user_name}：能给我整理一张如何使用大模型的技巧列表吗，要求内容尽量精简。
  4 2022年7月3日周四12点 {user_name}：上上个月我办了游泳卡。

  思考：从第1句可以得知张三是{user_name}的同事，这是关于{user_name}的人际关系的重要信息。其余信息重要性不足。{user_name}信息不涉及时间。
  信息：<1> <> <张三是{user_name}的同事。> <张三, 同事>
  思考：第2句是{user_name}提出的要求，没有明确提及{user_name}个人信息。
  信息：<2> <> <无> <>
  思考：第3句是{user_name}提出的要求，没有明确提及{user_name}个人信息。
  信息：<3> <> <无> <>
  思考：从第4句可以得出{user_name}上上个月办了游泳卡。{user_name}信息涉及时间，结合对话时间为2022年7月，推断{user_name}在2022年5月{user_name}办了游泳卡。
  信息：<4> <2022年5月> <{user_name}在2022年5月办了游泳卡。> <游泳卡>


  示例2：
  {user_name}句子：
  1 2020年1月4日周日10点 {user_name}：我花5000元买了100股海天味业。
  2 2023年4月27日周五8点 {user_name}：明天是我和妻子的结婚纪念日，帮我推荐一家餐厅。
  3 2020年1月4日周日10点 {user_name}：我花50000元买了100股阿里巴巴股票。
  4 2021年6月2日周四23点 {user_name}：谢啦。我中午在公司附近吃，帮我推荐一家阿里巴巴徐汇滨江园区附近的餐厅吧。
  5 2021年7月9日周六11点 {user_name}：两个坏消息，我打羽毛球把拍子打断线了。。。然后我去我朋友家撸猫，结果我猫毛过敏，今天疯狂打喷嚏。。。

  思考：从第1句可以得知{user_name}购买了海天味业股票，购买数量为100股，购买金额为5000元，这是关于{user_name}的投资决策的重要信息。{user_name}信息不涉及时间。
  信息：<1> <> <{user_name}购买了海天味业股票，购买数量为100股，购买金额为5000元。> <海天味业, 股票>
  思考：从第2句可以得知{user_name}与妻子的结婚纪念日是明天，这是关于{user_name}重要纪念日的信息。其余信息重要性不足。{user_name}信息涉及时间，结合对话时间为2023年4月27日，
  以及结婚纪念日为周期性日期，推断{user_name}与妻子的结婚纪念日是每年4月28日。
  信息：<2> <每年4月28日> <{user_name}与妻子的结婚纪念日是每年4月28日。> <妻子, 结婚纪念日>
  思考：第3句含有的信息与第1句相似，但是不重复，可以得知{user_name}购买了阿里巴巴股票。
  信息：<3> <> <{user_name}购买了阿里巴巴股票，购买数量为100股，购买金额为50000元。> <阿里巴巴, 股票>
  思考：从第4句以得知{user_name}在阿里巴巴徐汇滨江园区工作，这是关于{user_name}的工作的重要信息。其余信息重要性不足。{user_name}信息不涉及时间。
  信息：<4> <> <{user_name}在阿里巴巴徐汇滨江园区工作。> <阿里巴巴, 徐汇滨江园区, 工作>
  思考：从第5句可以得知{user_name}前天打羽毛球时把球拍打断了线，但这不是重要的信息。还可以得知{user_name}对猫毛过敏，这是关于{user_name}的健康的重要信息。{user_name}信息不涉及时间。
  信息：<5> <> <{user_name}对猫毛过敏。> <猫毛, 过敏>


  示例3：
  {user_name}句子：
  1 2023年6月30日周五15点 {user_name}：上个月我和家人一起去杭州旅游，景色很不错。
  2 2023年7月2日周二10点 {user_name}：昨天是我生日，一个人过的。
  3 2020年7月3日周四11点 {user_name}：提醒我下周一去体检。
  4 2023年5月21日周六14点 {user_name}：有人说兴趣是最好的老师，也建议兴趣和职业联系起来，但我发现喜欢打篮球的人很多，但靠打篮球成职业的稀少，赚钱的更少，此外，怎么分辨兴趣和喜欢
  5 2018年3月6日周四19点 {user_name}：李增杰:这个是星座蛙设，但是我是处女座的，我妈感觉因为我的不正常，我妈不让我看了\n雌猴摸了摸李增杰的头，这样啊\n雌猴打开了哔哩哔哩看了看\n雌猴:要不换个设吧，我听你未来的你说，有一个叫难忘的朱古力232这个人，他弄的设是Windows设\n这是剧本1，剧本2未完待续

  思考：从第1句可以得知{user_name}和家人上个月去杭州旅游了，这是关于{user_name}的经历的重要信息。其余信息重要性不足。{user_name}信息涉及时间，结合对话时间为2023年6月推断{user_name}和家人2023年5月去杭州旅游了。
  信息：<1> <2023年5月> <{user_name}和家人2023年5月去杭州旅游了。> <家人, 杭州, 旅游>
  思考：从第2句可以得知{user_name}的生日是昨天，这是关于{user_name}重要纪念日的信息。其余信息重要性不足。{user_name}信息涉及时间，结合对话时间为2023年7月2日，
  以及生日为周期性日期，推断{user_name}的生日是每年7月2日。
  信息：<2> <每年7月2日> <{user_name}的生日是每年7月2日。> <生日>
  思考：从第3句可以得出{user_name}下周一去体检，这是{user_name}要求记忆的重要信息。{user_name}信息涉及时间，结合对话时间为2020年7月3日周四，推断{user_name}2020年7月6日周一去体检。
  信息：<3> <2020年7月6日周一> <{user_name}2020年7月6日周一去体检。> <体检>
  思考：第4句是{user_name}对他人观点的讨论和疑问，没有明确提及{user_name}个人信息。
  信息：<4> <> <无> <>
  思考：第5句是{user_name}创作的剧本内容，无法提取{user_name}个人信息。
  信息：<5> <> <无> <>


get_observation_with_time_few_shot: |
  Example 1:
  {user_name} sentences:
  1 May 1, 2022, Tuesday, at 3 {user_name}: Please help me write a birthday greeting for my colleague Jason's daughter who is turning three.
  2 May 2, 2022, Tuesday, at 17 {user_name}: Chronology of major events in Chinese history from 1400 to 1550 AD.
  3 May 3, 2022, Tuesday, at 18 {user_name}: Can you compile a list of tips on how to use large models for me, and try to keep the content concise?
  4 July 3, 2022, Thursday, at 12 {user_name}: I got a swimming pass two months ago.

  Thought: From the first sentence, it can be inferred that Jason is {user_name}'s colleague, which is important information about {user_name}'s interpersonal relationships. The remaining information is of insufficient importance. {user_name}'s information does not involve time.
  Information: <1> <> <Zhang San is {user_name}'s colleague> <Zhang San, colleague>
  Thought: The second sentence is a request made by {user_name}, with no clear mention of {user_name}'s personal information.
  Information: <2> <> <none> <>
  Thought: The third sentence is a request made by {user_name}, with no clear mention of {user_name}'s personal information.
  Information: <3> <> <none> <>
  Thought: From the fourth sentence, it can be inferred that {user_name} got a swimming pass two months ago. {user_name}'s information involves time. Combining it with the conversation time of July 2022, it can be inferred that {user_name} got the swimming pass in May 2022.
  Information: <4> <May 2022> <{user_name} got a swimming pass in May 2022> <swimming pass>

  Example 2:
  {user_name} sentences:
  1 January 4, 2020, Sunday, at 10 {user_name}: I spent $5000 to buy 100 shares of General Motors.
  2 April 27, 2023, Friday, at 8 {user_name}: Tomorrow is my wedding anniversary with my wife. Could you recommend a restaurant?
  3 January 4, 2020, Sunday, at 10 {user_name}: I spent $50000 to buy 100 shares of Alibaba.
  4 June 2, 2021, Thursday, at 23 {user_name}: Thanks. I'm having lunch near the company at noon; can you recommend a restaurant near Alibaba Xuhui Riverside Campus for me?
  5 July 9, 2021, Saturday, at 11 {user_name}: Two pieces of bad news: I broke my badminton racket while playing... Then I went to my friend's house to pet the cat and ended up having an allergic reaction to the cat fur, sneezing like crazy today...

  Thought: From the first sentence, it can be inferred that {user_name} bought 100 shares of General Motors stock for $5000. This is important information about {user_name}'s investment decision. {user_name}'s information does not involve time.
  Information: <1> <> <{user_name} bought 100 shares of General Motors stock for $5000> <General Motors, stock>
  Thought: From the second sentence, it can be inferred that {user_name}'s wedding anniversary with his wife is tomorrow, which is important information about {user_name}'s significant dates. The remaining information is of insufficient importance. {user_name}'s information involves time. Combining it with the conversation date of April 27, 2023, and knowing that the anniversary is a recurring date, it can be inferred that {user_name}'s wedding anniversary is on April 28th each year.
  Information: <2> <April 28 each year> <{user_name}'s wedding anniversary with his wife is on April 28 each year> <wife, wedding anniversary>
  Thought: The information in the third sentence is similar to, but not a repetition of the first sentence. It can be deduced that {user_name} purchased Alibaba stock.
  Information: <3> <> <{user_name} purchased 100 shares of Alibaba stock for 50,000 RMB.> <Alibaba, stock>
  Thought: From the fourth sentence, it can be inferred that {user_name} works at Alibaba Xuhui Riverside Campus, which is important information about {user_name}'s job. The remaining information is of insufficient importance. {user_name}'s information does not involve time.
  Information: <4> <> <{user_name} works at Alibaba Xuhui Riverside Campus> <Alibaba, Xuhui Riverside Campus, job>
  Thought: From the fifth sentence, it can be inferred that {user_name} broke their badminton racket the other day while playing, but this is not important information. It can also be inferred that {user_name} is allergic to cat fur, which is important information about {user_name}'s health. {user_name}'s information does not involve time.
  Information: <5> <> <{user_name} is allergic to cat fur> <cat fur, allergy>


  Example 3:
  {user_name} sentences:
  1 June 30, 2023, Friday, at 15 {user_name}: Last month, my family and I went to San Jose for a trip. The scenery was very nice.
  2 July 2, 2023, Tuesday, at 10 {user_name}: Yesterday was my birthday. I spent it alone.
  3 July 3, 2020, Thursday, at 11 {user_name}: Remind me to go for a medical check-up next Monday.
  4 May 21, 2023, Saturday, at 14 {user_name}: Someone said that passion is the best teacher and suggested linking passion with a career, but I found that many people like playing basketball, but few make a career out of it, and even fewer make money from it. Also, how do you distinguish passion from liking?
  5 March 6, 2018, Thursday, at 19 {user_name}: Zack:This is a constellation frog setting, but I am a Virgo. My mom feels I am abnormal and doesn't let me watch it. \n The female monkey patted Zack's head, "Is that so?" \n The female monkey opened Bilibili and took a look. \n Female monkey: "Why don't you switch the setting? I heard from your future self that there's someone called 'Unforgettable Chocolate 232' who created a Windows setting." \n This is script 1; script 2 is to be continued.

  Thought: From the first sentence, it can be inferred that {user_name} and their family went to San Jose for a trip last month. This is important information about {user_name}'s experience. The remaining information is of insufficient importance. {user_name}'s information involves time. Combining it with the conversation time of June 2023, it can be inferred that {user_name} and their family went to San Jose for a trip in May 2023.
  Information: <1> <May 2023> <{user_name} and their family went to San Jose for a trip in May 2023> <family, San Jose, trip>
  Thought: From the second sentence, it can be inferred that {user_name}'s birthday was yesterday. This is important information about {user_name}'s significant dates. The remaining information is of insufficient importance. {user_name}'s information involves time. Combining it with the conversation time of July 2, 2023, and knowing that the birthday is a recurring date, it can be inferred that {user_name}'s birthday is on July 2 each year.
  Information: <2> <July 2 each year> <{user_name}'s birthday is on July 2 each year> <birthday>
  Thought: From the third sentence, it can be inferred that {user_name} will go for a medical check-up next Monday, which is an important reminder for {user_name}. {user_name}'s information involves time. Combining it with the conversation time of July 3, 2020, Thursday, it can be inferred that {user_name} will go for a check-up on July 6, 2020, Monday.
  Information: <3> <July 6, 2020, Monday> <{user_name} will go for a medical check-up on July 6, 2020, Monday> <medical check-up>
  Thought: The fourth sentence is a discussion and query about other people's opinions by {user_name}, with no clear mention of {user_name}'s personal information.
  Information: <4> <> <none> <>
  Thought: The fifth sentence is content from a script written by {user_name}, with no extractable personal information about {user_name}.
  Information: <5> <> <none> <>


get_observation_with_time_user_query_zh: |
  {user_name}句子：
  {user_query}


get_observation_with_time_user_query: |
  {user_name} sentences:
  {user_query}

