README.md

metadata

language:
  - zh
license: cc-by-4.0
task_categories:
  - text-classification
tags:
  - legal
  - taiwan
  - tax
size_categories:
  - 1M<n<10M

Disputability Datasets for Taiwanese Administrative Tax Cases (DDTAT)

Overview

This dataset contains over 50,000 administrative litigation judgments from Taiwan, primarily focusing on tax law cases. It provides a rich resource for legal natural language processing (LegalNLP), specifically for tasks such as disputability detection, legal judgment prediction, and document structure analysis.

The dataset is hosted on Hugging Face Hub: hochienH/DDTAT

The dataset is organized into two configurations:

1. judgements: Full text and metadata for each judgment.
2. sentences: Over 4.5 million sentences annotated with disputability labels.

Dataset Structure

1. Judgements (Config: judgements)

• Content: Full text and metadata of judgments.
• Fields:
  • JID: Unique Judgment ID (e.g., KSBA,102,訴,424,20150325,3)
  • JYEAR: Case Year
  • JCASE: Case Type (e.g., 訴, 簡)
  • JNO: Case Number
  • JDATE: Judgment Date
  • JTITLE: Case Reason/Title (e.g., 綜合所得稅)
  • JFULL: Full text of the judgment
  • DISPUTABILITY: Document-level label

2. Sentences (Config: sentences)

• Content: Annotated sentences.
• Fields:
  • 檔名: Corresponding Judgment ID
  • 句子編號: Sentence Sequence ID
  • 句子內容: Text content of the sentence
  • DISPUTABILITY: Sentence-level label

Usage

You can easily load the dataset using the Hugging Face datasets library.

from datasets import load_dataset

# Load Sentences
ds_sentences = load_dataset("hochienH/DDTAT", "sentences")
print(ds_sentences['train'][0])

# Load Judgments
ds_judgements = load_dataset("hochienH/DDTAT", "judgements")
print(ds_judgements['train'][0])

Statistics

Data Volume

• Total Judgments: 52,993
• Total Sentences: 4,479,889

Length Distribution (Characters)

Level	Mean	Median	Std Dev	Q1 (25%)	Q3 (75%)
Sentence	101.09	76.00	92.36	42.00	132.00
Judgment	11,487.13	9,207.00	8,257.11	N/A	N/A

Disputability Label Distribution

The dataset is imbalanced, with the majority of sentences falling into two categories (Label 1 and Label 2).

Label	Count	Percentage
1	2,360,486	52.69%
2	1,761,577	39.32%
3	123,971	2.77%
4	199,589	4.46%
5	20,359	0.45%
Others	~13,000	< 0.3%

Top 10 Case Titles (Reasons)

The dataset is heavily focused on tax administration.

1. Individual Income Tax (綜合所得稅)
2. Profit-seeking Enterprise Income Tax (營利事業所得稅)
3. Business Tax (營業稅)
4. Gift Tax (贈與稅)
5. Land Value Tax (地價稅)
6. Estate Tax (遺產稅)
7. Land Value Increment Tax (土地增值稅)
8. House Tax (房屋稅)
9. Customs Tariff Classification (進口貨物核定稅則號別)
10. Income Tax Act (所得稅法)

Visualizations

1. Disputability Distribution by Case Title

Distribution of disputability labels across the top 10 most frequent case types. Labels 1 and 2 are highlighted in lighter colors.

2. Overall Judgment Disputability

Overall proportion of disputability labels across the entire dataset.

3. Length Statistics

Distribution of sentence lengths and full judgment lengths (Top 99%).