--- license: cc-by-nc-4.0 task_categories: - text-classification task_ids: - multi-class-classification language: - te multilinguality: - monolingual size_categories: - n<1K pretty_name: Padyam2GadyamMeterClassification tags: - poetry - telugu - meter-classification - chandassu - text-classification - mteb - poetrymteb - embedding-evaluation annotations_creators: - expert-generated source_datasets: - TeluguLLMResearch/Padyam2Gadyam configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* default: true dataset_info: - config_name: default features: - name: id dtype: string - name: poem dtype: string - name: label dtype: int64 - name: label_name dtype: string splits: - name: train num_examples: 468 - name: test num_examples: 118 --- # Padyam2GadyamMeterClassification Single-label **Telugu poetic meter (chandassu) classification** for PoetryMTEB embedding evaluation, derived from [Padyam2Gadyam](https://huggingface.co/datasets/TeluguLLMResearch/Padyam2Gadyam). ## Dataset Card | Item | Description | |------|-------------| | **Source** | [TeluguLLMResearch/Padyam2Gadyam](https://huggingface.co/datasets/TeluguLLMResearch/Padyam2Gadyam); paper [arXiv:2606.02806](https://arxiv.org/abs/2606.02806) | | **Languages** | Telugu (`te`) | | **Size** | train=468; test=118 (no validation; MTEB Classification uses train→fit, test→score) | | **Classes** | 7 meters with frequency ≥ 10 | | **Filtering** | Dropped 14 poems in rare meters (count < 10); raw=600 → kept=586 | | **Splits** | Stratified by meter ≈ 80% / 19% (`train` / `test`), seed=42 | | **License** | [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (same as upstream) | | **Evaluation metrics** | Classification on embeddings: **accuracy**, **macro/weighted F1** | --- ## Features | Field | Type | Description | |-------|------|-------------| | `id` | string | Example id | | `poem` | string | Classical Telugu poem text | | `label` | int64 | Meter class index (0 … C−1) | | `label_name` | string | Meter name in Telugu | Codebook: `label_taxonomy.json`. ### Label inventory (kept) | id | label_name | gloss | count | |---:|------------|-------|------:| | 0 | కందం | Kandam (坎达体) | 216 | | 1 | ఉత్పలమాల | Utpalamāla (优钵罗鬘) | 115 | | 2 | చంపకమాల | Champakamāla (瞻波迦鬘) | 79 | | 3 | మత్తేభము | Mattebhamu (醉象律) | 79 | | 4 | శార్దూలము | Śārdūlamu (虎律) | 43 | | 5 | తేటగీతి | Tēṭagīti (澄歌体) | 35 | | 6 | ఆటవెలది | Āṭaveladi (戏舞体) | 19 | ### Dropped meters (count < 10) | meter | count | |-------|------:| | సీసము+తేటగీతి | 6 | | మాలిని | 2 | | చంపకమాల-పంచపాది | 2 | | తరళము | 1 | | ఉత్పలమాల-పంచపాది | 1 | | ఉత్సాహము | 1 | | మత్తకోకిల | 1 | --- ## Construction method 1. Load [TeluguLLMResearch/Padyam2Gadyam](https://huggingface.co/datasets/TeluguLLMResearch/Padyam2Gadyam). 2. Count `Meter`; keep classes with frequency ≥ 10. 3. Map kept meters to contiguous `label` ids (frequency-descending order). 4. Stratified train/test split by meter (no validation split). --- ## How to load ```python from datasets import load_dataset ds = load_dataset("PoetryMTEB/Padyam2GadyamMeterClassification") print(ds["test"][0]["label_name"], ds["test"][0]["poem"][:60]) ``` For embedding evaluation, encode `poem`, fit a classifier on `train` labels, score on `test`. --- ## License Distributed under **Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)**, consistent with the upstream dataset. --- ## Citation / provenance ```bibtex @misc{kranti2026translatingclassicalpoetrymodern, title={Translating Classical Poetry into Modern Prose}, author={Chalamalasetti Kranti and Sowmya Vajjala}, year={2026}, eprint={2606.02806}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2606.02806}, } ``` - Dataset: [https://huggingface.co/datasets/TeluguLLMResearch/Padyam2Gadyam](https://huggingface.co/datasets/TeluguLLMResearch/Padyam2Gadyam) - Paper: [https://arxiv.org/abs/2606.02806](https://arxiv.org/abs/2606.02806) - This Hub packaging: `PoetryMTEB/Padyam2GadyamMeterClassification`