| --- |
| language: |
| - bn |
| - en |
| - gu |
| - hi |
| - kn |
| - ml |
| - mr |
| - or |
| - pa |
| - ta |
| - te |
| - ur |
| license: cc-by-4.0 |
| size_categories: |
| - 1M<n<10M |
| pretty_name: Pralekha |
| dataset_info: |
| features: |
| - name: n_id |
| dtype: string |
| - name: doc_id |
| dtype: string |
| - name: lang |
| dtype: string |
| - name: text |
| dtype: string |
| splits: |
| - name: aligned |
| num_bytes: 10274361211 |
| num_examples: 1566404 |
| - name: unaligned |
| num_bytes: 4466506637 |
| num_examples: 783197 |
| download_size: 5812005886 |
| dataset_size: 14740867848 |
| configs: |
| - config_name: default |
| data_files: |
| - split: aligned |
| path: data/aligned-* |
| - split: unaligned |
| path: data/unaligned-* |
| tags: |
| - data-mining |
| - parallel-corpus |
| - document-alignment |
| --- |
| # Pralekha |
|
|
| PRALEKHA is a large-scale benchmark for evaluating document-level alignment techniques. It includes 2M+ documents, covering 11 Indic languages and English, with a balanced mix of aligned and unaligned pairs. |
| [](https://arxiv.org/abs/2411.19096) [](https://huggingface.co/datasets/ai4bharat/Pralekha) [](https://github.com/AI4Bharat/Pralekha) |
|
|
| --- |
| ## Dataset Description |
|
|
| PRALEKHA covers 12 languages—Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu, Urdu, and English. It includes a mixture of high- and medium-resource languages, covering 11 different scripts. The dataset spans two broad domains: **news bulletins** and **podcast scripts**, offering both written and spoken forms of data. All the data is human-written or human-verified, ensuring high quality. |
|
|
| The dataset has a **1:2 ratio of aligned to unaligned document pairs**, making it ideal for benchmarking cross-lingual document alignment techniques. |
|
|
| ### Data Sources |
|
|
| 1. **News Bulletins:** Data was custom-scraped from the [Indian Press Information Bureau (PIB)](https://pib.gov.in) website. Documents were aligned by matching bulletin IDs, which interlink bulletins across languages. |
| 2. **Podcast Scripts:** Data was sourced from [Mann Ki Baat](https://www.pmindia.gov.in/en/mann-ki-baat), a radio program hosted by the Indian Prime Minister. This program, originally spoken in Hindi, was manually transcribed and translated into various Indian languages. |
|
|
| ### Dataset Size Statistics |
|
|
| | Split | Number of Documents | Size (bytes) | |
| |---------------|---------------------|--------------------| |
| | **Aligned** | 1,566,404 | 10,274,361,211 | |
| | **Unaligned** | 783,197 | 4,466,506,637 | |
| | **Total** | 2,349,601 | 14,740,867,848 | |
|
|
| ### Language-wise Statistics |
|
|
| | Language | Aligned Documents | Unaligned Documents | Total Documents | |
| |----------------|-------------------|---------------------|-----------------| |
| | Bengali (`bn`) | 95,813 | 47,906 | 143,719 | |
| | English (`en`) | 298,111 | 149,055 | 447,166 | |
| | Gujarati (`gu`)| 67,847 | 33,923 | 101,770 | |
| | Hindi (`hi`) | 204,809 | 102,404 | 307,213 | |
| | Kannada (`kn`) | 61,998 | 30,999 | 92,997 | |
| | Malayalam (`ml`)| 67,760 | 33,880 | 101,640 | |
| | Marathi (`mr`) | 135,301 | 67,650 | 202,951 | |
| | Odia (`or`) | 46,167 | 23,083 | 69,250 | |
| | Punjabi (`pa`) | 108,459 | 54,229 | 162,688 | |
| | Tamil (`ta`) | 149,637 | 74,818 | 224,455 | |
| | Telugu (`te`) | 110,077 | 55,038 | 165,115 | |
| | Urdu (`ur`) | 220,425 | 110,212 | 330,637 | |
|
|
| ### Data Fields |
|
|
| Each data sample includes: |
|
|
| - **`n_id`:** Unique identifier for aligned document pairs. |
| - **`doc_id`:** Unique identifier for individual documents. |
| - **`lang`:** Language of the document (ISO-3 code). |
| - **`text`:** The textual content of the document. |
|
|
| --- |
|
|
| ## License |
|
|
| This dataset is released under the **CC BY 4.0** license. For more information, see [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/). |
|
|
| --- |
|
|
| ## Contact |
|
|
| For any questions or feedback, please contact: |
|
|
| - Raj Dabre ([raj.dabre@cse.iitm.ac.in](mailto:raj.dabre@cse.iitm.ac.in)) |
| - Sanjay Suryanarayanan ([sanj.ai@outlook.com](mailto:sanj.ai@outlook.com)) |
| - Haiyue Song ([haiyue.song@nict.go.jp](mailto:haiyue.song@nict.go.jp)) |
| - Mohammed Safi Ur Rahman Khan ([safikhan2000@gmail.com](mailto:safikhan2000@gmail.com)) |
|
|
| Please get in touch with us for any copyright concerns. |
|
|
| --- |
