Duplicate from ai4bharat/Pralekha

Co-authored-by: Mohammed Safi Ur Rahman Khan <safikhan@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+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:
+- config_name: alignable
+  features:
+  - name: n_id
+    dtype: string
+  - name: doc_id
+    dtype: string
+  - name: lang
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
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+  - name: eng
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+  - name: guj
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+    num_examples: 67847
+  - name: hin
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+  - name: kan
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+  - name: mal
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+  - name: mar
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+  - name: ori
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+    num_examples: 46167
+  - name: pan
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+  - name: tam
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+    num_examples: 149637
+  - name: tel
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+    num_examples: 110077
+  - name: urd
+    num_bytes: 1199225480
+    num_examples: 220425
+  download_size: 3954199760
+  dataset_size: 10274361211
+- config_name: dev
+  features:
+  - name: src_lang
+    dtype: string
+  - name: tgt_lang
+    dtype: string
+  - name: src_txt
+    dtype: string
+  - name: tgt_txt
+    dtype: string
+  splits:
+  - name: eng_ben
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+    num_examples: 1000
+  - name: eng_guj
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+    num_examples: 1000
+  - name: eng_hin
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+    num_examples: 1000
+  - name: eng_kan
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+    num_examples: 1000
+  - name: eng_mal
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+    num_examples: 1000
+  - name: eng_mar
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+    num_examples: 1000
+  - name: eng_ori
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+    num_examples: 1000
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+    num_examples: 1000
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+    num_examples: 1000
+  - name: eng_urd
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+    num_examples: 1000
+  download_size: 48192585
+  dataset_size: 117088106
+- config_name: test
+  features:
+  - name: src_lang
+    dtype: string
+  - name: tgt_lang
+    dtype: string
+  - name: src_txt
+    dtype: string
+  - name: tgt_txt
+    dtype: string
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+    num_examples: 1000
+  - name: eng_kan
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+    num_examples: 1000
+  - name: eng_ori
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+    num_examples: 1000
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+    num_examples: 1000
+  download_size: 55844958
+  dataset_size: 134876785
+- config_name: train
+  features:
+  - name: src_lang
+    dtype: string
+  - name: src_txt
+    dtype: string
+  - name: tgt_lang
+    dtype: string
+  - name: tgt_txt
+    dtype: string
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+  - name: eng_ori
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+    num_examples: 37321
+  - name: eng_pan
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+  - name: eng_tel
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+    num_examples: 101109
+  - name: eng_urd
+    num_bytes: 1843885193
+    num_examples: 211229
+  download_size: 5224096653
+  dataset_size: 12446952678
+- 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
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+    num_examples: 47906
+  - name: eng
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+    num_examples: 149055
+  - name: guj
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+  - name: hin
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+  - name: kan
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+  - name: mal
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+  - name: mar
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+  - name: ori
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+    num_examples: 23083
+  - name: pan
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+    num_examples: 54229
+  - name: tam
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+  - name: tel
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+    num_examples: 55038
+  - name: urd
+    num_bytes: 644995094
+    num_examples: 110212
+  download_size: 1855179179
+  dataset_size: 4474912799
+configs:
+- config_name: alignable
+  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
+  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
+  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: train
+  data_files:
+  - split: eng_ben
+    path: train/eng_ben-*
+  - split: eng_guj
+    path: train/eng_guj-*
+  - split: eng_hin
+    path: train/eng_hin-*
+  - split: eng_kan
+    path: train/eng_kan-*
+  - split: eng_mal
+    path: train/eng_mal-*
+  - split: eng_mar
+    path: train/eng_mar-*
+  - split: eng_ori
+    path: train/eng_ori-*
+  - split: eng_pan
+    path: train/eng_pan-*
+  - split: eng_tam
+    path: train/eng_tam-*
+  - split: eng_tel
+    path: train/eng_tel-*
+  - split: eng_urd
+    path: train/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:
+- parallel-corpus
+- document-alignment
+- machine-translation
+task_categories:
+- 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">
+    <img src="https://img.shields.io/badge/huggingface-Pralekha-yellow" alt="HuggingFace">
+  </a>
+  <a href="https://github.com/AI4Bharat/Pralekha">
+    <img src="https://img.shields.io/badge/github-Pralekha-blue" alt="GitHub">
+  </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">
+  </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-Indic Pairs. 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.)
+- **`doc_id`:** Unique identifier for individual documents.
+- **`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:
+
+```
+@inproceedings{suryanarayanan-etal-2025-pralekha,
+    title = "{PRALEKHA}: Cross-Lingual Document Alignment for {I}ndic Languages",
+    author = "Suryanarayanan, Sanjay  and Song, Haiyue  and Khan, Mohammed Safi Ur Rahman  and Kunchukuttan, Anoop  and Dabre, Raj",
+    booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
+    month = dec,
+    year = "2025",
+    address = "Mumbai, India",
+    publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
+    url = "https://aclanthology.org/2025.ijcnlp-long.37/",
+    pages = "662--676"
+    }
+```
+
+## 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:
+
+- Sanjay Suryanarayanan ([sanj.ai@outlook.com](mailto:sanj.ai@outlook.com))
+- Haiyue Song ([haiyue.song@nict.go.jp](mailto:haiyue.song@nict.go.jp)) 
+- Raj Dabre ([raj.dabre@cse.iitm.ac.in](mailto:raj.dabre@cse.iitm.ac.in))  
+
+Please get in touch with us for any copyright concerns.

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