Update README.md

README.md

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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+---
+# TeSent_Benchmark-Dataset
+
+**TeSent_Benchmark-Dataset** is a large-scale, open Telugu sentiment classification benchmark, developed to advance robust and interpretable sentiment analysis research for low-resource languages. While primarily created for sentence-level sentiment classification, this dataset is also a valuable resource for general text classification and related tasks in Telugu NLP.
+
+---
+
+## Overview
+
+- **Language:** Telugu
+- **Size:** 22,505 labeled examples
+- **Task:** Sentence-level, three-class sentiment classification (positive, negative, neutral)
+- **Explainability:** Each example is annotated with human-provided rationales—text snippets that justify the assigned sentiment label.
+
+---
+
+## Features
+
+- **Labeled Sentences:** Each data sample contains a Telugu sentence and its sentiment label (positive, negative, or neutral).
+- **Human-Annotated Rationales:** For every sentence, annotators have highlighted the specific text fragments that they found decisive for their sentiment decision, enabling explainable AI research.
+- **Versatility:** While designed for sentiment classification, the dataset is suitable for broader text classification, rationale extraction, and other NLP tasks in Telugu.
+
+---
+
+## Format
+
+| Content           | Rationale                        | Label                                |
+|-------------------|----------------------------------|--------------------------------------|
+| Telugu sentence   | Human-annotated text snippet(s)  | Sentiment class (positive/negative/neutral) |
+
+---
+
+## Applications
+
+- **Benchmarking Telugu Sentiment Models:** Establish a standard for model comparison and progress tracking.
+- **Explainability Research:** Train and evaluate models that can provide human-interpretable sentiment explanations.
+- **Text Classification & NLP Tasks:** Useful for training and evaluating models for general text classification, rationale extraction, and other Telugu natural language processing tasks.
+
+---
+
+## Citation
+
+If you use this dataset in your research, please cite as follows:
+
+```
+@inproceedings{tesent,
+  title={TeSent: A Benchmark Dataset for Explainable Sentiment Classification in Telugu},
+  author={Your Name and Collaborators},
+  year={2025},
+  note={https://github.com/DSL-13-SRMAP/TeSent_Benchmark-Dataset}
+}