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README.md

@@ -1,33 +1,101 @@
+
 ---
-dataset_info:
-  features:
-  - name: doc_id
-    dtype: int64
-  - name: question_en
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: level_0
-    dtype: string
-  - name: level_1
-    dtype: string
-  - name: level_2
-    dtype: string
-  - name: level_3
-    dtype: string
-  - name: level_4
-    dtype: string
-  - name: level_5
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 1651069
-    num_examples: 2091
-  download_size: 694495
-  dataset_size: 1651069
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+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}
+}
+```