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README.md
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@@ -189,6 +189,8 @@ The dataset was created by collecting approximately 33,000 case rulings from [op
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- 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.
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- This is the first version of the dataset, and future versions will incorporate additional metadata and employ more refined labeling techniques.
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## Labeling Methodology
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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.
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- 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.
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- This is the first version of the dataset, and future versions will incorporate additional metadata and employ more refined labeling techniques.
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## Labeling Methodology
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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.
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