|
|
| --- |
| language: |
| - en |
| - te |
| license: apache-2.0 |
| task_categories: |
| - question-answering |
| - text-retrieval |
| - text-generation |
| pretty_name: Telugu QA Paraphrases |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Telugu QA Paraphrases |
|
|
| A synthetic multilingual query-rewriting dataset for evaluating retrieval robustness under Telugu-English code mixing. |
|
|
| ## Dataset Description |
|
|
| This dataset extends an existing Telugu QA dataset by generating multiple query variants with increasing levels of Telugu-English code mixing. |
|
|
| Each example contains: |
|
|
| - `question` : Original English question |
| - `answer` : Ground-truth answer |
| - `level_0` : English paraphrase |
| - `level_1` : Light Telugu-English code mixing |
| - `level_2` : Moderate Telugu-English code mixing |
| - `level_3` : Heavy Telugu-English code mixing |
| - `level_4` : Romanized Telugu |
| - `level_5` : Telugu script |
|
|
| ## Motivation |
|
|
| Multilingual embedding models are often evaluated on pure English or fully translated queries. |
|
|
| Real-world users frequently write: |
|
|
| - Telugu-English code mixed text |
| - Romanized Telugu |
| - Mixed-script queries |
|
|
| This dataset enables evaluation of retrieval robustness across progressively increasing code-mixing levels. |
|
|
| ## Example |
|
|
| ```json |
| { |
| "question": "How do I apply for a passport in India?", |
| "answer": "...", |
| "level_0": "How can I apply for an Indian passport?", |
| "level_1": "భారతదేశంలో పాస్పోర్ట్ ఎలా అప్లై చెయ్యాలి?", |
| "level_2": "India-lo passport apply process enti?", |
| "level_3": "భారత్ పాస్పోర్ట్ అప్లికేషన్ ఎలా చేయాలి?", |
| "level_4": "India passport apply ela?", |
| "level_5": "భారతదేశ పాస్పోర్ట్ కోసం ఎలా అప్లై చేయాలి?" |
| } |
| ``` |
|
|
| ## Intended Uses |
|
|
| - Multilingual retrieval |
| - Dense retrieval evaluation |
| - RAG benchmarking |
| - Code-mixed query understanding |
| - Embedding model robustness analysis |
|
|
| ## Source Dataset |
|
|
| This dataset was generated from: |
|
|
| https://huggingface.co/datasets/gurumurthy3/Legal-FAQ |
|
|
| Please cite and credit the original dataset creators. |
|
|
| ## Generation |
|
|
| Query variants were generated using Sarvam-M and subsequently filtered for semantic preservation. |
|
|
| ## Limitations |
|
|
| The generated paraphrases may contain: |
|
|
| - Imperfect transliteration |
| - Script mixing |
| - Translation artifacts |
| - Semantic drift in a small number of examples |
|
|
| Manual validation is recommended for benchmark creation. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{telugu_qa_paraphrases, |
| title={Telugu QA Paraphrases}, |
| author={Suhas Koheda}, |
| year={2026} |
| } |
| ``` |
|
|
