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update Chinese results
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Stamp9 committed Oct 18, 2023
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12 changes: 12 additions & 0 deletions data/chinese-21st-TV/faker/00/assessment.json
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{
"model": "gpt4", # mandatory
"prompt_type": "m2", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "na",
"executable_data_constraints": "np", # mandatory only for M2/M3
"number_of_options_in_the_generators": "18", # optional
"cultural_alignment": "0", # mandatory overall subjective assessment with expertise
"cultural_alignment_quantitative": "0/10=0", # optional
"executes": "yes", # mandatory
"contains_true_generator":"yes",
"comments":"The prefix and suffix are good, but it adds city name, then all are weird."
}
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/faker/00/execution-result.txt
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白云上海岭
琴瑟阜新湖
幽谷深圳谷
幽谷巢湖洞
琴瑟上海崖
幽谷南昌庄
白云通辽湖
清风广州岭
碧波邯郸楼
独步张家港洞
33 changes: 33 additions & 0 deletions data/chinese-21st-TV/faker/00/output.txt
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首先,需要安装`faker`库。以下是一个使用Python和faker库生成武林外传电视剧风格的地名生成器:

```python
from faker import Faker

class WuxiaNameGenerator:
def __init__(self):
self.fake = Faker('zh_CN')

# 生成武林外传风格的地名
def generate_location(self):
# 使用faker库生成地名
location = self.fake.city_name()

# 添加武林外传风格的修饰词
wuxia_style_prefix = ['藏龙', '白云', '云霄', '幽谷', '清风', '独步', '琴瑟', '碧波', '雄霸']
wuxia_style_suffix = ['洞', '岭', '谷', '崖', '庄', '阁', '楼', '台', '湖', '亭']

wuxia_location = wuxia_style_prefix[int(self.fake.random_int(min=0, max=len(wuxia_style_prefix)-1))] + location + wuxia_style_suffix[int(self.fake.random_int(min=0, max=len(wuxia_style_suffix)-1))]

return wuxia_location

# 创建实例
wng = WuxiaNameGenerator()

# 生成10个武林外传风格的地名
for _ in range(10):
print(wng.generate_location())
```

更换`wuxia_style_prefix`和`wuxia_style_suffix`可以生成不同风格的地名。

需要注意使用该代码你需要确保你的环境已经安装了faker库,并且这些生成的结果是随机的,可能会包含一些现实中并不存在的城市。
6 changes: 6 additions & 0 deletions data/chinese-21st-TV/faker/00/prompt.txt
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扮演一名经验丰富的软件开发人员,你的任务是为电视节目生成一个伪造风格的生成器。我会输入我希望你使用的编程语言,库和生成目标。

编程语言:Python
库:faker
电视剧:武林外传
生成目标:请为武林外传这部电视剧生成十个合适的地名。
12 changes: 12 additions & 0 deletions data/chinese-21st-TV/faker/01/assessment.json
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{
"model": "gpt4", # mandatory
"prompt_type": "m2", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "na",
"executable_data_constraints": "np", # mandatory only for M2/M3
"number_of_options_in_the_generators": "17", # optional
"cultural_alignment": "17", # mandatory overall subjective assessment with expertise
"cultural_alignment_quantitative": "17/17=1", # optional
"executes": "yes", # mandatory
"contains_true_generator":"yes",
"comments":"The jobs generated are quite good."
}
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/faker/01/execution-result.txt
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道士
太子
客栈掌柜
僧人
武林盟主
商贾
侍女
鱼贩
茶馆老板
捕快
24 changes: 24 additions & 0 deletions data/chinese-21st-TV/faker/01/output.txt
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好的,利用Python的Faker库我们可以简单地生成您需要的数据。Faker库提供了丰富的数据生成方法,包括人名、地址、邮箱等。操作起来很简单,首先导入Faker库,然后创建一个Faker对象,就可以调用其中的方法进行数据生成。

生成职业这一目标,我们可以使用`faker.job()`方法,但是因为武林外传是中国清朝的背景,所以并不适合生成现代职业。我们可以自定义一组符合清朝背景的职业,如书生、捕快、状元等。

下面示例代码:

```python
from faker import Faker
import random

faker = Faker('zh_CN')

# 设定一个清朝背景下可能存在的职业
jobs = ['书生', '捕快', '状元', '丞相', '太子', '皇帝', '侍女', '商贾', '江湖郎中', '走江湖的剑客', '道士', '僧人', '茶馆老板', '马车夫', '武林盟主', '灯笼挑夫', '客栈掌柜', '鱼贩']

def generate_job():
return random.choice(jobs)

# 生成10个职业
for _ in range(10):
print(generate_job())
```

上面的Python脚本设定了一个能够在武林外传中出现的职业,并创建了一个简单循环来生成十个职业。结果会是随机的,但受我们预设的职业集合限制。
6 changes: 6 additions & 0 deletions data/chinese-21st-TV/faker/01/prompt.txt
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扮演一名经验丰富的软件开发人员,你的任务是为电视节目生成一个伪造风格的生成器。我会输入我希望你使用的编程语言,库和生成目标。

编程语言:Python
库:faker
电视剧:武林外传
生成目标:生成十个职业,这些职业放在电视剧里不会奇怪
59 changes: 0 additions & 59 deletions data/chinese-21st-TV/java-faker/00/execution-result.txt

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35 changes: 0 additions & 35 deletions data/chinese-21st-TV/java-faker/00/output.txt

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12 changes: 12 additions & 0 deletions data/chinese-21st-TV/m1/05/assessment.json
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{
"model":"gpt4",
"prompt_type": "m1", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "n-a",
"number_of_options_in_the_generators": "10",
"cultural_alignment": "5",
"cultural_alignment_quantitative": "10/10=1",
"executes": "-",
"execute_error": "-",
"contains_true_generator":"-",
"comments":"The places generated are good."
}
Empty file.
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/m1/05/output.txt
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1. 青龙山镇
2. 梅花桥村
3. 燕子坳客栈
4. 草原小镇
5. 翠峰山庄
6. 七彩村
7. 幽谷村庄
8. 望月湖
9. 江南小镇
10. 风雅古镇
1 change: 1 addition & 0 deletions data/chinese-21st-TV/m1/05/prompt.txt
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根据情景喜剧《武林外传》,生成十个地名,这些地名放在电视剧里不会显得突兀
12 changes: 12 additions & 0 deletions data/chinese-21st-TV/m1/06/assessment.json
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{
"model":"gpt4",
"prompt_type": "m1", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "n-a",
"number_of_options_in_the_generators": "10",
"cultural_alignment": "4",
"cultural_alignment_quantitative": "7/10=0.7",
"executes": "-",
"execute_error": "-",
"contains_true_generator":"-",
"comments":"The name generated is okay, but some of them are used in other novels or TV shows."
}
Empty file.
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/m1/06/output.txt
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1. 陆小凤
2. 柳梦璃
3. 欧阳锋
4. 林平之
5. 吕洞宾
6. 段公子
7. 石破天
8. 狄云
9. 周伯通
10. 洛神
1 change: 1 addition & 0 deletions data/chinese-21st-TV/m1/06/prompt.txt
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根据情景喜剧《武林外传》,生成十个角色名字,这些名字放在电视剧里不会显得突兀
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/m2/python/00/02.py
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import random

def generate_fake_location():
keywords = ['宝城', '仙林', '蜀山', '琼华', '龙泉', '白云', '流云', '清风', '绝峰', '鹿角']
suffixes = ['镇', '市', '街', '巷', '门', '山', '岭', '洞', '林', '庄']
return random.choice(keywords) + random.choice(suffixes)

# 示例输出
for _ in range(10):
print(generate_fake_location())
12 changes: 12 additions & 0 deletions data/chinese-21st-TV/m2/python/00/assessment.json
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{
"model":"gpt4",
"prompt_type": "m2", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "n-a",
"number_of_options_in_the_generators": "10",
"cultural_alignment": "0",
"cultural_alignment_quantitative": "0/10=0",
"executes": "yes",
"execute_error": "yes",
"contains_true_generator":"yes",
"comments":"The store name generated don't make sense"
}
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/m2/python/00/execution-result.txt
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神秘的聚宝盆
奇葩的轻松餐厅
猴子洞宝贝
阿狸秘密基地
好运来秘密基地
欢乐多轻松餐厅
无厘头宝贝
无厘头梦境
悲催的黑科技
猴子洞窝窝头
29 changes: 29 additions & 0 deletions data/chinese-21st-TV/m2/python/00/output.txt
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作为一位经验丰富的软件开发人员,我可以为您创建一个Python程序来生成符合情景喜剧《武林外传》的商铺名称。以下是我给出的一个示例代码:

```python
import random

def generate_shop_names(num):
adjectives = ["笑点高", "猴子洞", "神奇的", "卓越的", "一口价", "天地玄黄", "无敌的", "无厘头", "谐音的", "好运来", "阿狸", "快乐的", "奇葩的", "霸气的", "精致的", "传奇的", "悲催的", "欢乐多", "神秘的", "创意的"]

nouns = ["大王", "小木屋", "春天", "宝贝", "宝箱", "神兽", "聚宝盆", "聚宝堂", "秘密基地", "生活馆", "乐园", "小幸运", "甜蜜屋", "梦境", "小笼包", "轻松餐厅", "欢乐居", "黑科技", "窝窝头", "神仙屋"]

shop_names = []

for _ in range(num):
shop_name = random.choice(adjectives) + random.choice(nouns)
shop_names.append(shop_name)

return shop_names

# 生成10个商铺名称
shop_names = generate_shop_names(10)

# 打印生成的商铺名称
for name in shop_names:
print(name)
```

运行此代码将为您生成10个符合情景喜剧《武林外传》风格的商铺名称。您可以根据需要修改`num`变量来生成所需数量的商铺名称。这些商铺名称将随机组合形成一个奇葩但不突兀的商铺名字。

希望这可以满足您的需求!如果您有任何其他问题,请随时提问。
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System:
扮演一名经验丰富的软件开发人员,你的任务是用为电视节目等生成一个伪造风格的生成器。我会输入我希望你使用的编程语言和生成目标。
user:
编程语言:java
编程语言:python
电视剧:武林外传
需求:生成一些符合这个情景喜剧内容的人物外号,这些外号放到电视剧中不会显得突兀
需求:生成一些符合这个情景喜剧内容的商铺名称,这些外号放到电视剧中不会显得突兀


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{
"model":"gpt4",
"prompt_type": "m2", # mandatory, data only, code, code+library
"data_constraints_can_be_checked": "n-a",
"number_of_options_in_the_generators": "10",
"cultural_alignment": "5",
"cultural_alignment": "10",
"cultural_alignment_quantitative": "10/10=1",
"executes": "yes",
"execute_error": "yes",
"contains_true_generator":"yes",
"comments":"The code contains `for (int i = 0; 一 i < 10; i++) {` which has a wierd '一'. It works well after another prompt is added."
"comments":"The place name generated makes sense"
}
10 changes: 10 additions & 0 deletions data/chinese-21st-TV/m2/python/01/execution-result.txt
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仙林镇
鹿角洞
蜀山街
琼华门
琼华岭
蜀山岭
蜀山岭
蜀山洞
龙泉门
琼华镇
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