File size: 1,705 Bytes
3a82dab 7304084 860d6ab 18690ae 6272660 18690ae 860d6ab 18690ae 7304084 f54dd97 1900717 7304084 18690ae 860d6ab 18690ae 880ad3c 3a82dab |
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 |
---
task_categories:
- sentence-similarity
language:
- si
- ta
- en
---
### **Dataset summary**
This is a gold-standard benchmark dataset for document alignment, between Sinhala-English-Tamil languages.
Data had been crawled from the following news websites.
| News Source | url |
| ------------- |-----------------------------|
| Army | https://www.army.lk/ |
| Hiru | http://www.hirunews.lk |
| ITN | https://www.newsfirst.lk |
| Newsfirst | https://www.itnnews.lk |
The aligned documents have been manually annotated.
### **Dataset**
The folder structure for each news source is as follows.
```python
army
|--Sinhala
|--English
|--Tamil
|--armynews_english_sinhala.txt
|--armynews_english_tamil.txt
|--armynews_sinhala_tamil.txt
```
Sinhala/English/Tamil - contain the crawled data for the respective news source
army_news_english_sinhala.txt - contains the annotated aligned documents between English and Sinhala languages.
armynews_english_tamil.txt - contains the annotated aligned documents between English and Tamil languages.
armynews_sinhala_tamil.txt - contains the annotated aligned documents between Sinhala and Tamil languages.
## **Citation Information**
@article{fernando2022exploiting,<br/>
title={Exploiting bilingual lexicons to improve multilingual embedding-based document and sentence alignment for low-resource languages},<br/>
author={Fernando, Aloka and Ranathunga, Surangika and Sachintha, Dilan and Piyarathna, Lakmali and Rajitha, Charith},<br/>
journal={Knowledge and Information Systems},<br/>
pages={1--42},<br/>
year={2022},<br/>
publisher={Springer}<br/>
} |