|
--- |
|
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: |
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- config_name: alignable |
|
features: |
|
- name: n_id |
|
dtype: string |
|
- name: doc_id |
|
dtype: string |
|
- name: lang |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
splits: |
|
- name: ben |
|
num_bytes: 651961117 |
|
num_examples: 95813 |
|
- name: eng |
|
num_bytes: 1048149692 |
|
num_examples: 298111 |
|
- name: guj |
|
num_bytes: 549286108 |
|
num_examples: 67847 |
|
- name: hin |
|
num_bytes: 1754308559 |
|
num_examples: 204809 |
|
- name: kan |
|
num_bytes: 567860764 |
|
num_examples: 61998 |
|
- name: mal |
|
num_bytes: 498894372 |
|
num_examples: 67760 |
|
- name: mar |
|
num_bytes: 961277740 |
|
num_examples: 135301 |
|
- name: ori |
|
num_bytes: 397642857 |
|
num_examples: 46167 |
|
- name: pan |
|
num_bytes: 872586190 |
|
num_examples: 108459 |
|
- name: tam |
|
num_bytes: 858335433 |
|
num_examples: 149637 |
|
- name: tel |
|
num_bytes: 914832899 |
|
num_examples: 110077 |
|
- name: urd |
|
num_bytes: 1199225480 |
|
num_examples: 220425 |
|
download_size: 3954199760 |
|
dataset_size: 10274361211 |
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- config_name: dev |
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features: |
|
- name: src_text |
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dtype: string |
|
- name: tgt_text |
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dtype: string |
|
splits: |
|
- name: eng_ben |
|
num_bytes: 11878032 |
|
num_examples: 1000 |
|
- name: eng_guj |
|
num_bytes: 12114408 |
|
num_examples: 1000 |
|
- name: eng_hin |
|
num_bytes: 11866493 |
|
num_examples: 1000 |
|
- name: eng_kan |
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num_bytes: 12737616 |
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num_examples: 1000 |
|
- name: eng_mal |
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num_bytes: 13282361 |
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num_examples: 1000 |
|
- name: eng_mar |
|
num_bytes: 12562695 |
|
num_examples: 1000 |
|
- name: eng_ori |
|
num_bytes: 12440443 |
|
num_examples: 1000 |
|
- name: eng_pan |
|
num_bytes: 11887954 |
|
num_examples: 1000 |
|
- name: eng_tam |
|
num_bytes: 10889623 |
|
num_examples: 1000 |
|
- name: eng_tel |
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num_bytes: 12862241 |
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num_examples: 1000 |
|
- name: eng_urd |
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num_bytes: 9313209 |
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num_examples: 1000 |
|
download_size: 49754255 |
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dataset_size: 131835075 |
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- config_name: test |
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features: |
|
- name: src_text |
|
dtype: string |
|
- name: tgt_text |
|
dtype: string |
|
splits: |
|
- name: eng_ben |
|
num_bytes: 11326293 |
|
num_examples: 1000 |
|
- name: eng_guj |
|
num_bytes: 11754732 |
|
num_examples: 1000 |
|
- name: eng_hin |
|
num_bytes: 11572603 |
|
num_examples: 1000 |
|
- name: eng_kan |
|
num_bytes: 12210417 |
|
num_examples: 1000 |
|
- name: eng_mal |
|
num_bytes: 12750095 |
|
num_examples: 1000 |
|
- name: eng_mar |
|
num_bytes: 12260214 |
|
num_examples: 1000 |
|
- name: eng_ori |
|
num_bytes: 11926414 |
|
num_examples: 1000 |
|
- name: eng_pan |
|
num_bytes: 11534797 |
|
num_examples: 1000 |
|
- name: eng_tam |
|
num_bytes: 11072385 |
|
num_examples: 1000 |
|
- name: eng_tel |
|
num_bytes: 12530011 |
|
num_examples: 1000 |
|
- name: eng_urd |
|
num_bytes: 9196555 |
|
num_examples: 1000 |
|
download_size: 49449543 |
|
dataset_size: 128134516 |
|
- config_name: unalignable |
|
features: |
|
- name: n_id |
|
dtype: string |
|
- name: doc_id |
|
dtype: string |
|
- name: lang |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
splits: |
|
- name: ben |
|
num_bytes: 273391595 |
|
num_examples: 47906 |
|
- name: eng |
|
num_bytes: 420307531 |
|
num_examples: 149055 |
|
- name: guj |
|
num_bytes: 214351582 |
|
num_examples: 33923 |
|
- name: hin |
|
num_bytes: 683869386 |
|
num_examples: 102404 |
|
- name: kan |
|
num_bytes: 189633814 |
|
num_examples: 30999 |
|
- name: mal |
|
num_bytes: 192394324 |
|
num_examples: 33880 |
|
- name: mar |
|
num_bytes: 428715921 |
|
num_examples: 67650 |
|
- name: ori |
|
num_bytes: 111986274 |
|
num_examples: 23083 |
|
- name: pan |
|
num_bytes: 328564948 |
|
num_examples: 54229 |
|
- name: tam |
|
num_bytes: 614171222 |
|
num_examples: 74818 |
|
- name: tel |
|
num_bytes: 372531108 |
|
num_examples: 55038 |
|
- name: urd |
|
num_bytes: 644995094 |
|
num_examples: 110212 |
|
download_size: 1855179179 |
|
dataset_size: 4474912799 |
|
configs: |
|
- config_name: alignable |
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data_files: |
|
- split: ben |
|
path: alignable/ben-* |
|
- split: eng |
|
path: alignable/eng-* |
|
- split: guj |
|
path: alignable/guj-* |
|
- split: hin |
|
path: alignable/hin-* |
|
- split: kan |
|
path: alignable/kan-* |
|
- split: mal |
|
path: alignable/mal-* |
|
- split: mar |
|
path: alignable/mar-* |
|
- split: ori |
|
path: alignable/ori-* |
|
- split: pan |
|
path: alignable/pan-* |
|
- split: tam |
|
path: alignable/tam-* |
|
- split: tel |
|
path: alignable/tel-* |
|
- split: urd |
|
path: alignable/urd-* |
|
- config_name: dev |
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data_files: |
|
- split: eng_ben |
|
path: dev/eng_ben-* |
|
- split: eng_guj |
|
path: dev/eng_guj-* |
|
- split: eng_hin |
|
path: dev/eng_hin-* |
|
- split: eng_kan |
|
path: dev/eng_kan-* |
|
- split: eng_mal |
|
path: dev/eng_mal-* |
|
- split: eng_mar |
|
path: dev/eng_mar-* |
|
- split: eng_ori |
|
path: dev/eng_ori-* |
|
- split: eng_pan |
|
path: dev/eng_pan-* |
|
- split: eng_tam |
|
path: dev/eng_tam-* |
|
- split: eng_tel |
|
path: dev/eng_tel-* |
|
- split: eng_urd |
|
path: dev/eng_urd-* |
|
- config_name: test |
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data_files: |
|
- split: eng_ben |
|
path: test/eng_ben-* |
|
- split: eng_guj |
|
path: test/eng_guj-* |
|
- split: eng_hin |
|
path: test/eng_hin-* |
|
- split: eng_kan |
|
path: test/eng_kan-* |
|
- split: eng_mal |
|
path: test/eng_mal-* |
|
- split: eng_mar |
|
path: test/eng_mar-* |
|
- split: eng_ori |
|
path: test/eng_ori-* |
|
- split: eng_pan |
|
path: test/eng_pan-* |
|
- split: eng_tam |
|
path: test/eng_tam-* |
|
- split: eng_tel |
|
path: test/eng_tel-* |
|
- split: eng_urd |
|
path: test/eng_urd-* |
|
- config_name: unalignable |
|
data_files: |
|
- split: ben |
|
path: unalignable/ben-* |
|
- split: eng |
|
path: unalignable/eng-* |
|
- split: guj |
|
path: unalignable/guj-* |
|
- split: hin |
|
path: unalignable/hin-* |
|
- split: kan |
|
path: unalignable/kan-* |
|
- split: mal |
|
path: unalignable/mal-* |
|
- split: mar |
|
path: unalignable/mar-* |
|
- split: ori |
|
path: unalignable/ori-* |
|
- split: pan |
|
path: unalignable/pan-* |
|
- split: tam |
|
path: unalignable/tam-* |
|
- split: tel |
|
path: unalignable/tel-* |
|
- split: urd |
|
path: unalignable/urd-* |
|
tags: |
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- parallel-corpus |
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- document-alignment |
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- machine-translation |
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task_categories: |
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- translation |
|
--- |
|
|
|
# Pralekha: Cross-Lingual Document Alignment for Indic Languages |
|
|
|
<div style="display: flex; gap: 10px;"> |
|
<a href="https://arxiv.org/abs/2411.19096"> |
|
<img src="https://img.shields.io/badge/arXiv-2411.19096-B31B1B" alt="arXiv"> |
|
</a> |
|
<a href="https://huggingface.co/datasets/ai4bharat/Pralekha"> |
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<img src="https://img.shields.io/badge/huggingface-Pralekha-yellow" alt="HuggingFace"> |
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</a> |
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<a href="https://github.com/AI4Bharat/Pralekha"> |
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<img src="https://img.shields.io/badge/github-Pralekha-blue" alt="GitHub"> |
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</a> |
|
<a href="https://creativecommons.org/licenses/by/4.0/"> |
|
<img src="https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey" alt="License: CC BY 4.0"> |
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</a> |
|
</div> |
|
|
|
**Pralekha** is a large-scale parallel document dataset spanning across **11 Indic languages** and **English**. It comprises over **3 million** document pairs, with **1.5 million** being English-centric. This dataset serves both as a benchmark for evaluating **Cross-Lingual Document Alignment (CLDA)** techniques and as a domain-specific parallel corpus for training document-level **Machine Translation (MT)** models in Indic Languages. |
|
|
|
--- |
|
|
|
## Dataset Description |
|
|
|
**Pralekha** covers 12 languages—Bengali (`ben`), Gujarati (`guj`), Hindi (`hin`), Kannada (`kan`), Malayalam (`mal`), Marathi (`mar`), Odia (`ori`), Punjabi (`pan`), Tamil (`tam`), Telugu (`tel`), Urdu (`urd`), and English (`eng`). It includes a mixture of high- and medium-resource languages, covering 11 different scripts. The dataset spans two broad domains: **News Bulletins** ([Indian Press Information Bureau (PIB)](https://pib.gov.in)) and **Podcast Scripts** ([Mann Ki Baat (MKB)](https://www.pmindia.gov.in/en/mann-ki-baat)), offering both written and spoken forms of data. All the data is human-written or human-verified, ensuring high quality. |
|
|
|
While this accounts for `alignable` (parallel) documents, In real-world scenarios, multilingual corpora often include `unalignable` documents. To simulate this for CLDA evaluation, we sample `unalignable` documents from [Sangraha Unverified](https://huggingface.co/datasets/ai4bharat/sangraha/viewer/unverified), selecting 50% of Pralekha’s size to maintain a 1:2 ratio of `unalignable` to `alignable` documents. |
|
|
|
For Machine Translation (MT) tasks, we first randomly sample 1,000 documents from the `alignable` subset per English-Indic language pair for each development (dev) and test set, ensuring a good distribution of varying document lengths. After excluding these sampled documents, we use the remaining documents as the training set for training document-level machine translation models. |
|
|
|
--- |
|
|
|
## Data Fields |
|
|
|
### Alignable & Unalignable Set: |
|
|
|
- **`n_id`:** Unique identifier for `alignable` document pairs (Random `n_id`'s are assigned for the `unalignable` set.) |
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- **`doc_id`:** Unique identifier for individual documents. |
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- **`lang`:** Language of the document (ISO 639-3 code). |
|
- **`text`:** The textual content of the document. |
|
|
|
### Train, Dev & Test Set: |
|
|
|
- **`src_lang`:** Source Language (eng) |
|
- **`src_text`:** Source Language Text |
|
- **`tgt_lang`:** Target Language (ISO 639-3 code) |
|
- **`tgt_text`:** Target Language Text |
|
|
|
--- |
|
|
|
## Usage |
|
|
|
You can load specific **subsets** and **splits** from this dataset using the `datasets` library. |
|
|
|
### Load an entire subset |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset("ai4bharat/Pralekha", data_dir="<subset>") |
|
# <subset> = alignable, unalignable, train, dev & test. |
|
``` |
|
|
|
### Load a specific split within a subset |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset("ai4bharat/Pralekha", data_dir="<subset>/<lang>") |
|
# <subset> = alignable, unalignable ; <lang> = ben, eng, guj, hin, kan, mal, mar, ori, pan, tam, tel, urd. |
|
``` |
|
```python |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset("ai4bharat/Pralekha", data_dir="<subset>/eng_<lang>") |
|
# <subset> = train, dev & test ; <lang> = ben, guj, hin, kan, mal, mar, ori, pan, tam, tel, urd. |
|
``` |
|
|
|
--- |
|
|
|
## Data Size Statistics |
|
|
|
| Split | Number of Documents | Size (bytes) | |
|
|---------------|---------------------|--------------------| |
|
| **Alignable** | 1,566,404 | 10,274,361,211 | |
|
| **Unalignable** | 783,197 | 4,466,506,637 | |
|
| **Total** | 2,349,601 | 14,740,867,848 | |
|
|
|
## Language-wise Statistics |
|
|
|
| Language (`ISO-3`) | Alignable Documents | Unalignable Documents | Total Documents | |
|
|---------------------|-------------------|---------------------|-----------------| |
|
| Bengali (`ben`) | 95,813 | 47,906 | 143,719 | |
|
| English (`eng`) | 298,111 | 149,055 | 447,166 | |
|
| Gujarati (`guj`) | 67,847 | 33,923 | 101,770 | |
|
| Hindi (`hin`) | 204,809 | 102,404 | 307,213 | |
|
| Kannada (`kan`) | 61,998 | 30,999 | 92,997 | |
|
| Malayalam (`mal`) | 67,760 | 33,880 | 101,640 | |
|
| Marathi (`mar`) | 135,301 | 67,650 | 202,951 | |
|
| Odia (`ori`) | 46,167 | 23,083 | 69,250 | |
|
| Punjabi (`pan`) | 108,459 | 54,229 | 162,688 | |
|
| Tamil (`tam`) | 149,637 | 74,818 | 224,455 | |
|
| Telugu (`tel`) | 110,077 | 55,038 | 165,115 | |
|
| Urdu (`urd`) | 220,425 | 110,212 | 330,637 | |
|
|
|
--- |
|
|
|
# Citation |
|
If you use Pralekha in your work, please cite us: |
|
|
|
``` |
|
@article{suryanarayanan2024pralekha, |
|
title={Pralekha: An Indic Document Alignment Evaluation Benchmark}, |
|
author={Suryanarayanan, Sanjay and Song, Haiyue and Khan, Mohammed Safi Ur Rahman and Kunchukuttan, Anoop and Khapra, Mitesh M and Dabre, Raj}, |
|
journal={arXiv preprint arXiv:2411.19096}, |
|
year={2024} |
|
} |
|
``` |
|
|
|
## License |
|
|
|
This dataset is released under the [**CC BY 4.0**](https://creativecommons.org/licenses/by/4.0/) license. |
|
|
|
|
|
## Contact |
|
|
|
For any questions or feedback, please contact: |
|
|
|
- Raj Dabre ([[email protected]](mailto:[email protected])) |
|
- Sanjay Suryanarayanan ([[email protected]](mailto:[email protected])) |
|
- Haiyue Song ([[email protected]](mailto:[email protected])) |
|
- Mohammed Safi Ur Rahman Khan ([[email protected]](mailto:[email protected])) |
|
|
|
Please get in touch with us for any copyright concerns. |
