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menesnas/SemanticTextualSimilarityDataset

Semantic Textual Similarity (STS) Dataset (Turkish) This repository contains a Turkish Semantic Textual Similarity (STS) dataset created as part of a university assignment on semantic similarity, sentence embeddings, and vector representations in Natural Language Processing (NLP). Authors Muhammet Enes Nas Salih Dede About The purpose of this project was to gain practical experience with: Semantic Textual Similarity (STS) Sentence Embeddings… See the full description on the dataset page: https://huggingface.co/datasets/menesnas/SemanticTextualSimilarityDataset.

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Dataset Card

Semantic Textual Similarity (STS) Dataset (Turkish)

This repository contains a Turkish Semantic Textual Similarity (STS) dataset created as part of a university assignment on semantic similarity, sentence embeddings, and vector representations in Natural Language Processing (NLP).

Authors

  • Muhammet Enes Nas
  • Salih Dede

About

The purpose of this project was to gain practical experience with:

  • Semantic Textual Similarity (STS)
  • Sentence Embeddings
  • Vector Representations
  • Similarity Scoring
  • NLP Dataset Preparation

The dataset consists of Turkish sentence pairs annotated with a semantic similarity score ranging from 0 to 100, where:

ScoreMeaning
0Completely unrelated
25Weak semantic relation
50Moderate similarity
75High similarity
100Semantically equivalent

Dataset Format

Each sample contains three fields:

ColumnDescription
sentence1First sentence
sentence2Second sentence
humanScoreHuman-annotated semantic similarity score (0–100)

Example:

json
{
  "sentence1": "Doktor ameliyata geç kaldı.",
  "sentence2": "Ameliyatı yapacak hekim gecikti.",
  "humanScore": 97.85
}

Intended Use

This dataset is intended for educational and research purposes, including:

  • Sentence Embedding models
  • Semantic Similarity prediction
  • Siamese Networks
  • SBERT fine-tuning
  • Embedding evaluation
  • NLP coursework

License

MIT License.