Datasets:
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license: apache-2.0
task_categories:
- feature-extraction
- text-classification
- token-classification
- translation
- summarization
- text-generation
- text2text-generation
- question-answering
language:
- sa
tags:
- code
pretty_name: Śrīmad Devī-bhāgavatam
size_categories:
- 10K<n<100K
---
# Dataset Card for srimad_devi_bhagavata_mahapurana
## Dataset Details
### Dataset Description
This dataset contains a complete, structured representation of the _Śrīmad Devī-bhāgavatam mahāpurāṇe_ in CSV format, broken down into Skandas, Adhyāyas, and individual ślokas. It is designed for NLP applications—including feature extraction, classification, translation, summarization, question-answering, and generation—on classical Sanskrit scripture.
- **Curated by:** [Aluminium](https://huggingface.co/13Aluminium)
- **Organization:** [Snskrt](https://huggingface.co/snskrt)
- **Shared by:** [Snskrt](https://huggingface.co/snskrt)
- **Language(s):** Sanskrit (ISO code: sa)
- **License:** Apache-2.0
- **Size:** ~18,702 ślokas
### Dataset Sources
- **Repository:** [huggingface.co/datasets/snskrt/Devi_Bhagavatam](https://huggingface.co/datasets/snskrt/Devi_Bhagavatam)
## Uses
### Direct Use
- Training and evaluating Sanskrit language models on classical hymn/text generation
- Building Sanskrit question-answering systems over Purāṇic content
- Machine translation between Sanskrit and modern languages
- Summarization and feature extraction of mythological scripture
### Out-of-Scope Use
- Modern colloquial or conversational Sanskrit tasks
## Dataset Structure
Each record in the CSV/JSON has these fields:
- `skanda` (string): Skanda number, e.g. `"1"`
- `adhyaya_number` (string): Adhyāya index, e.g. `"१.१"`
- `adhyaya_title` (string): Sanskrit chapter title
- `a_index` (int): auxiliary sequence index
- `m_index` (int): main sequence index
- `text` (string): full śloka text
## Dataset Creation
### Curation Rationale
To provide researchers with a fully parsed, program-friendly version of the Devi-Bhāgavata Mahāpurāṇa for a wide range of NLP tasks.
### Source Data
#### Data Collection and Processing
- Raw Sanskrit text obtained from the critical editions of Śrīmad Devī-bhāgavatam
- Parsed into JSON via custom Python scripts
- Converted to CSV with per-Skanda/Adhyāya logging
#### Who are the source data producers?
Original Purāṇic verses attributed to Vyāsa; digital encoding by Snskrt.
## Bias, Risks, and Limitations
- Classical text only—no modern translations or commentary included.
- Possible editorial or typographical errors from digitization.
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