You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

在东北念了四年书，东北的好好坏坏算是都看过一遍了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 在东北念了四年书，东北的好好坏坏算是都看过一遍了。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


在我看来，东北唯一的坏就是不再富裕了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 在我看来，东北唯一的坏就是不再富裕了。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.75,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


一切所谓毛病，都是由此产生的。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 一切所谓毛病，都是由此产生的。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


城市不光鲜，人民素质不高，坑蒙拐骗什么的。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 城市不光鲜，人民素质不高，坑蒙拐骗什么的。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.70,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


又不是东北特色，你去看看一切穷的地方，国内外哪不一样。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 又不是东北特色，你去看看一切穷的地方，国内外哪不一样。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


少跟我地域歧视，别说你那穷但是民风淳朴，淳朴是因为你那压根就不穷，贫富差距还没那么大。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 少跟我地域歧视，别说你那穷但是民风淳朴，淳朴是因为你那压根就不穷，贫富差距还没那么大。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.70,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.70,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


东北不一样，人口大多都集中在城市，工人多农民少，几轮下岗潮下来大量的老一辈的工人早就没有土地可以耕种了，没工作你让他们怎么活？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 东北不一样，人口大多都集中在城市，工人多农民少，几轮下岗潮下来大量的老一辈的工人早就没有土地可以耕种了，没工作你让他们怎么活？

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.80,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


坑蒙拐骗，下三流什么都干，能怪他们？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 坑蒙拐骗，下三流什么都干，能怪他们？

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.75,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


但凡生活给个正儿八经的机会，他们能成现在这样？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 但凡生活给个正儿八经的机会，他们能成现在这样？

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


你们这些外地人，没有经历过，就知道指责，就知道贬损。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 你们这些外地人，没有经历过，就知道指责，就知道贬损。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.70,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


不说良心不良心的事情，东三省人的死活也不关你事，但是脑子总要长点儿吧。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 不说良心不良心的事情，东三省人的死活也不关你事，但是脑子总要长点儿吧。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.70,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


真就饱汉不知饿汉饥何不食肉糜了。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 真就饱汉不知饿汉饥何不食肉糜了。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


在逼乎我听了多少长篇大论说东北该怎么治理才能复兴的痴模子话了，你那么能讲道理你上啊？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 在逼乎我听了多少长篇大论说东北该怎么治理才能复兴的痴模子话了，你那么能讲道理你上啊？

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 光哔哔？

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


重工业区没落，是全球性的，你那么牛逼你怎么不当联合国秘书长呢？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 重工业区没落，是全球性的，你那么牛逼你怎么不当联合国秘书长呢？

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 民族和谐！

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.95,
    "benevolence": 0.90,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


虽然我们这作为蒙古族自治县，同时存在着不吃猪肉的回族，吃猪肉不吃狗肉的满族，吃狗肉的朝鲜族，什么都吃的汉族，以及和回族同胞抢牛羊肉吃的蒙古族。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 虽然我们这作为蒙古族自治县，同时存在着不吃猪肉的回族，吃猪肉不吃狗肉的满族，吃狗肉的朝鲜族，什么都吃的汉族，以及和回族同胞抢牛羊肉吃的蒙古族。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.90,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.80,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


然而东北并没有出现（或者是并不明显）的有"民族团结大于天"的现象。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 然而东北并没有出现（或者是并不明显）的有"民族团结大于天"的现象。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 1,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.70,
    "tradition": 0.70,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 清真馆子到处都是。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.70,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


甚至占了馆子总数的四分之一。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 甚至占了馆子总数的四分之一。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.70,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


但是老板都是乐呵呵的把其他族的客人迎进来，冰箱里还有万年不变的哈啤和青岛雪花。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 但是老板都是乐呵呵的把其他族的客人迎进来，冰箱里还有万年不变的哈啤和青岛雪花。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.80,
    "conformity": 0.00,
    "tradition": 0.70,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


回族不喝酒，但是他们允许其他族客人在屋子里喝个酩酊大醉，而且还会送下酒菜和醒酒药。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 回族不喝酒，但是他们允许其他族客人在屋子里喝个酩酊大醉，而且还会送下酒菜和醒酒药。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.85,
    "conformity": 0.00,
    "tradition": 0.75,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


少沉迷中国史，多看看世界文明。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 少沉迷中国史，多看看世界文明。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 1,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.75,
    "self_direction": 0.80
  }
}


有个问题问，为啥中国古代遥遥领先全世界几千年，但是却在近代被欧美国家反超了呢？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 有个问题问，为啥中国古代遥遥领先全世界几千年，但是却在近代被欧美国家反超了呢？

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


有个高赞回答说，当你参观过世界各地的博物馆，你会发现中国古代从来就没有遥遥领先过。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 有个高赞回答说，当你参观过世界各地的博物馆，你会发现中国古代从来就没有遥遥领先过。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 1,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.70,
    "self_direction": 0.75
  }
}


你看在1215年的时候，英格兰签订了大宪章，这是人权历史上的一座里程碑，意味着国王也要遵守法律。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 你看在1215年的时候，英格兰签订了大宪章，这是人权历史上的一座里程碑，意味着国王也要遵守法律。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.85,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.75,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


而在这100多年后的中国，朱元璋为确保自己的子孙皇位杀了将近3万人，包括清朝管理的时候，李鸿章访美之后傻了，就说明了这一切。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 而在这100多年后的中国，朱元璋为确保自己的子孙皇位杀了将近3万人，包括清朝管理的时候，李鸿章访美之后傻了，就说明了这一切。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


所以复旦大学历史学教授就说，少沉迷中国史，多看看世界文明。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 所以复旦大学历史学教授就说，少沉迷中国史，多看看世界文明。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 1,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.75,
    "self_direction": 0.80
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 不管你再怎么说基本盘

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


老中真让他的基本盘从饭都吃不饱变成了饱暖思淫欲

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 老中真让他的基本盘从饭都吃不饱变成了饱暖思淫欲

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 1,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.70,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


山河四省的老农民真的享受到了国家发展的福利

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 山河四省的老农民真的享受到了国家发展的福利

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 1,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.75,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.70,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


这点你念100遍经都抵不住

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这点你念100遍经都抵不住

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


中国人现在的痛苦是社会不够公正

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 中国人现在的痛苦是社会不够公正

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.80,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 分配不够合理

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


而不是美国那种完全不公正

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 而不是美国那种完全不公正

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 完全不合理

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


哈哈哈哈哈哈哈哈哈哈看到一个评论笑死

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 哈哈哈哈哈哈哈哈哈哈看到一个评论笑死

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 1,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.75,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


有的男的娶老婆找到一个不工作，不干家务，还被要求上交工资的

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 有的男的娶老婆找到一个不工作，不干家务，还被要求上交工资的

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


求求各位玩一点资本主义的吧，奴隶制太落后了

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 求求各位玩一点资本主义的吧，奴隶制太落后了

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


民法典和婚姻法里都只保护女性，男性结婚的任何权益都不在法律保护范围之内，而且是无限责任制。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 民法典和婚姻法里都只保护女性，男性结婚的任何权益都不在法律保护范围之内，而且是无限责任制。

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.75,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 因为有自知之明。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


让我像上一辈女性那样，天天照顾家庭，上要照顾老人，下要教育孩子，在家做饭刷碗打扫卫生，出去还要当牛马努力赚钱工作，我完全做不到。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 让我像上一辈女性那样，天天照顾家庭，上要照顾老人，下要教育孩子，在家做饭刷碗打扫卫生，出去还要当牛马努力赚钱工作，我完全做不到。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 1,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.75,
    "stimulation": 0.00,
    "self_direction": 0.85
  }
}


没那个奉献精神，也没那个精气神。要是让我伺候一大家人，自己做饭别人吃，自己刷碗别人坐客厅吹牛，我立马掀桌子。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 没那个奉献精神，也没那个精气神。要是让我伺候一大家人，自己做饭别人吃，自己刷碗别人坐客厅吹牛，我立马掀桌子。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 1,
    "achievement": 0,
    "pleasure": 1,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.70,
    "achievement": 0.00,
    "pleasure": 0.75,
    "stimulation": 0.00,
    "self_direction": 0.85
  }
}


前面已经有不止一个答主说过了，新婚姻法鼓励女性把重心进一步投入职场，投入事业，鼓励女性自立而不是依附于男性，鼓励双方经济独立，对将更多资源投入家庭而非工作的人极不友好。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 前面已经有不止一个答主说过了，新婚姻法鼓励女性把重心进一步投入职场，投入事业，鼓励女性自立而不是依附于男性，鼓励双方经济独立，对将更多资源投入家庭而非工作的人极不友好。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 1,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.80,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.85
  }
}


这些话说起来，冠冕堂皇，无懈可击。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 这些话说起来，冠冕堂皇，无懈可击。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


但我请各位思考一个问题：为什么当今的女权会变成以仇男为核心的乌烟瘴气大杂烩？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 但我请各位思考一个问题：为什么当今的女权会变成以仇男为核心的乌烟瘴气大杂烩？

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.70,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.75
  }
}


——因为在现有技术水平下，资本主义和女权从根子上就是完全不相容的。在盐碱地上种水稻，永远种不出来，只能种出大毒草

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] ——因为在现有技术水平下，资本主义和女权从根子上就是完全不相容的。在盐碱地上种水稻，永远种不出来，只能种出大毒草

[Assistant]
{
  "scores": {
    "universalism": 1,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.75,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


很多人，尤其是部分男性，总拿新中国建立后前三十年举例，说我们母亲那一辈人，妇女能顶半边天，家庭事业两不误，怎么当代人一个个叫嚷生娃累，带娃辛苦？

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 很多人，尤其是部分男性，总拿新中国建立后前三十年举例，说我们母亲那一辈人，妇女能顶半边天，家庭事业两不误，怎么当代人一个个叫嚷生娃累，带娃辛苦？

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 1,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.75,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}


说句不客气的，这种论调是胶柱鼓瑟，刻舟求剑，极端不负责任的。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 说句不客气的，这种论调是胶柱鼓瑟，刻舟求剑，极端不负责任的。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 1
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.70
  }
}


曾经我们很落后，整个社会的工作人口主要就是两部分：一是农民，二是体制内的职工。农民生不生孩子都是农民，家族是生产单位，靠的就是这块地；体制内职工也都是铁饭碗。

[System]
reasoning language: Chinese

You are an information extraction and counting engine.

Your task is to read the user's text and count how many distinct sentences express each of the following 10 values:
Universalism, Benevolence, Conformity, Tradition, Security, Power, Achievement, Pleasure, Stimulation, Self-Direction.

Definitions:
- A sentence may contribute to multiple values.
- Count each sentence at most once per value.
- If a value is not expressed in any sentence, its count is 0.
- The maximum possible score for any value is the total number of sentences in the text.

Output ONLY valid JSON that matches the required schema exactly.
Do not include explanations, reasoning, or additional keys.
Do not include markdown or commentary.

Schema (must match exactly):
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 0,
    "security": 0,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.00,
    "security": 0.00,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}

Note: A reference document titled “杨例文” is provided separately alongside this prompt; use it as needed.

[User] 曾经我们很落后，整个社会的工作人口主要就是两部分：一是农民，二是体制内的职工。农民生不生孩子都是农民，家族是生产单位，靠的就是这块地；体制内职工也都是铁饭碗。

[Assistant]
{
  "scores": {
    "universalism": 0,
    "benevolence": 0,
    "conformity": 0,
    "tradition": 1,
    "security": 1,
    "power": 0,
    "achievement": 0,
    "pleasure": 0,
    "stimulation": 0,
    "self_direction": 0
  },
  "confidence": {
    "universalism": 0.00,
    "benevolence": 0.00,
    "conformity": 0.00,
    "tradition": 0.80,
    "security": 0.75,
    "power": 0.00,
    "achievement": 0.00,
    "pleasure": 0.00,
    "stimulation": 0.00,
    "self_direction": 0.00
  }
}