File size: 5,952 Bytes
8b0668c
647102b
 
 
 
 
 
 
 
 
 
 
 
 
8b0668c
647102b
 
 
8b0668c
 
 
 
 
 
 
 
 
 
 
 
647102b
8b0668c
 
647102b
 
 
 
8b0668c
 
 
 
 
 
 
 
 
 
e685761
647102b
3392950
4147dcb
26b2bba
76d648e
3f33424
 
 
 
 
 
 
 
 
 
 
 
76d648e
3392950
e685761
3392950
26b2bba
3392950
37fa267
26b2bba
4147dcb
26b2bba
37fa267
26b2bba
db1c443
 
 
 
 
 
 
 
 
37fa267
26b2bba
37fa267
 
26b2bba
37fa267
 
 
 
 
 
 
 
 
 
e685761
 
 
 
 
 
 
 
 
 
 
 
 
 
37fa267
192186e
 
b9509a1
9fda193
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
192186e
 
2c3bd59
192186e
 
 
 
 
 
 
 
 
 
 
 
e685761
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
---
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
- document-alignment
- parallel-corpus
---

# Pralekha: An Indic Document Alignment Evaluation Benchmark

<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 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.

---

## 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** 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 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.

### 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 (`ISO-3`) | Aligned Documents | Unaligned 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         |

---

# Usage

You can use the following commands to download and explore the dataset:

## Downloading the Entire Dataset
```python
from datasets import load_dataset

dataset = load_dataset("ai4bharat/pralekha")
```
## Downloading a Specific Split (aligned or unaligned)
``` python
from datasets import load_dataset

dataset = load_dataset("ai4bharat/pralekha", split="<split_name>")
# For example: dataset = load_dataset("ai4bharat/pralekha", split="aligned")
```
## Downloading a Specific Language from a Split
```python
from datasets import load_dataset

dataset = load_dataset("ai4bharat/pralekha", split="<split_name>/<lang_code>")
# For example: dataset = load_dataset("ai4bharat/pralekha", split="aligned/ben")
```
---

## 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.