ebowwa/human-biases

--- license: apache-2.0 --- ``` from datasets import load_dataset, Dataset # Load and preprocess the dataset def formatting_prompts_func(examples): """ This function takes a dataset of examples and formats them into a list of text prompts. Args: examples (pandas.DataFrame): A DataFrame containing the dataset of examples. Returns: dict: A dictionary with a 'text' key containing the list of formatted text prompts. """ texts = [ # Create a formatted text prompt for each example f"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Bias Category:\n{bias_category}\n### Type:\n{type}\n### Real-World Examples:\n{real_world_example}\n### Relevant Disciplines:\n{relevant_discipline}\n### Bias Subtype:\n{bias_subtype}\n### Underlying Mechanism:\n{underlying_mechanism}\n### Debiasing Strategies:\n{debiasing_strategy}\n### Practical Applications:\n{practical_application}\n### Bias Strength:\n{bias_strength}\n### Decision-Making Stage:\n{decision_making_stage}\n### Consequences:\n{consequence}\n### Mitigation Techniques:\n{mitigation_technique}\n### Cognitive Process Involved:\n{cognitive_process_involved}\n### Potential Causes:\n{potential_cause}\n### Valence:\n{valence}\n### Domain:\n{domain}\n### Response:\n" for bias_category, type, real_world_example, relevant_discipline, bias_subtype, underlying_mechanism, debiasing_strategy, practical_application, bias_strength, decision_making_stage, consequence, mitigation_technique, cognitive_process_involved, potential_cause, valence, domain in zip( examples["Bias Category"], examples["Type"], examples["Real-World Examples"], examples["Relevant Disciplines"], examples["Bias Subtype"], examples["Underlying Mechanism"], examples["Debiasing Strategies"], examples["Practical Applications"], examples["Bias Strength"], examples["Decision-Making Stage"], examples["Consequences"], examples["Mitigation Techniques"], examples["Cognitive Process Involved"], examples["Potential Causes"], examples["Valence"], examples["Domain"], ) ] # Print the first example prompt print(texts[0]) return {"text": texts} # Load the dataset dataset = load_dataset("ebowwa/human-biases") dataset = dataset.map(formatting_prompts_func, batched=True) ```

原始信息汇总

数据集概述

数据集加载与预处理

• 加载函数: load_dataset("ebowwa/human-biases")
• 预处理函数: formatting_prompts_func

预处理函数详情

• 功能: 将数据集中的示例格式化为文本提示列表。
• 输入参数: examples (类型: pandas.DataFrame)
• 返回值: 包含格式化文本提示的字典，键为 text。

格式化文本提示的结构

• Bias Category: 偏见类别
• Type: 类型
• Real-World Examples: 现实世界示例
• Relevant Disciplines: 相关学科
• Bias Subtype: 偏见子类型
• Underlying Mechanism: 潜在机制
• Debiasing Strategies: 去偏见策略
• Practical Applications: 实际应用
• Bias Strength: 偏见强度
• Decision-Making Stage: 决策阶段
• Consequences: 后果
• Mitigation Techniques: 缓解技术
• Cognitive Process Involved: 涉及的认知过程
• Potential Causes: 潜在原因
• Valence: 效价
• Domain: 领域
• Response: 响应