---
license: apache-2.0
dataset_info:
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    dtype: string
  - name: hypothesis
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  - name: label
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  splits:
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    num_bytes: 1858442640
    num_examples: 474283
  - name: validation
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    num_examples: 5000
  - name: test
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  download_size: 725637794
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configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- sentence-similarity
language:
- tr
tags:
- legal
size_categories:
- 100K<n<1M
---

# Turkish Law NLI Dataset
This dataset is derived from case files of Turkish Commercial Courts and was prepared as part of a student project to contribute to the Turkish NLP literature.

## Source Data
The dataset was created by collecting approximately 33,000 case rulings from [open sources](https://emsal.uyap.gov.tr/) using web scraping methods. The dataset includes only the "summary" sections of the case rulings, where the reason for each lawsuit is typically described.

## Data Structure and Labeling
- The dataset was adapted for sentence similarity tasks, inspired by the [SNLI dataset](https://huggingface.co/datasets/stanfordnlp/snli). The goal of this project is to develop a semantic search model for identifying relevant precedent cases in legal settings.
- This is the first version of the dataset, and future versions will incorporate additional metadata and employ more refined labeling techniques.

![First image from tree](images/TTK_1.jpg) ![Second image from tree](images/TTK_2.jpg)
<div style="text-align: center; opacity: 0.7;">
  <p style="font-style: italic;">Some sections of the Tree Structure</p>
</div>

## Labeling Methodology
To establish relationships between case files, legal articles within each case were utilized. Only commercial cases governed by the [Turkish Commercial Code (TTK)](https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=6102&MevzuatTur=1&MevzuatTertip=5) are included. Articles from the TTK were aligned in a hierarchical structure, considering main and subheadings, and were transformed into a tree structure. The relationship between cases was determined by calculating distances between the articles they contain within this tree structure.

### Label Types
- **Entailment:** For each case, the 7 closest cases (with lower distances indicating closer relationships) were labeled as related.
- **Contradiction:** For each case, the 7 most distant cases were labeled as unrelated.
- **Neutral:** Each case was labeled as neutral with respect to the legal articles it contains.

## Contributors
- Mesut Demirel
- Recep Karabulut