iamjry's picture
Upload AI Basic Law training dataset
f86d9bd verified
|
Raw
History Blame Contribute Delete
2.79 kB
metadata
language:
  - zh
license: cc-by-4.0
task_categories:
  - question-answering
  - text-generation
tags:
  - legal
  - taiwan
  - ai-law
  - traditional-chinese
size_categories:
  - 1K<n<10K

台灣人工智慧基本法 訓練資料集

Taiwan AI Basic Law (人工智慧基本法) Q&A dataset for LLM finetuning.

Dataset Description

  • Language: Traditional Chinese (繁體中文)
  • Domain: Taiwan AI Basic Law (台灣人工智慧基本法), 20 articles
  • Format: JSONL with chat messages (user/assistant)
  • Publication Date: 民國115年(2026年)1月14日

Files

File Description Entries
train.jsonl Full training dataset with oversampling ~5000
fulltext.jsonl Clean article fulltext (20 articles) 38

Data Composition

Category Unique Repeat Purpose
Article Fulltext Q&A ~157 x15 Verbatim article text with topic anchors
Alias Recognition ~109 x10 「基本法」「AI基本法」→ 人工智慧基本法
Legislative Reasons ~35 x3 Background rationale
Topic Mapping ~20 x15 Article number ↔ topic
Comprehensive Q&A ~8 x15 Cross-article questions
Taiwan Context ~4 x15 Anti-hallucination (not Chinese law)
Publication Date ~22 x15-20 民國115年(2026年)1月14日
Article Reinforcement ~8 x20 Fix stubborn misalignment

Data Format

Each line is a JSON object with messages array (Mistral chat format, system prompt merged into user message):

{
  "messages": [
    {
      "role": "user",
      "content": "你是一位熟悉台灣人工智慧基本法的法律助理,請根據法條內容精確回答問題。\n\n請列出人工智慧基本法第3條全文"
    },
    {
      "role": "assistant",
      "content": "人工智慧基本法第3條(第三條,主題:人工智慧定義):「本法所稱人工智慧...」"
    }
  ]
}

Key Design Decisions

  1. Topic Anchors: Answers include 第X條(第X條,主題:YYY) to prevent article number misalignment
  2. Oversampling: Correct answers repeated 10-20x to override base model's prior knowledge
  3. Data Consistency: All entries use consistent year (民國115年/2026年) to avoid conflicting signals
  4. Anti-Hallucination: Explicit entries stating "Taiwan law, not Chinese law" and "20 articles total"

Usage

from datasets import load_dataset
dataset = load_dataset("json", data_files="train.jsonl")

Related

License

CC-BY-4.0