### **Dataset summary** This is a gold-standard benchmark dataset for sentence alignment, between Sinhala-English-Tamil languages. Data had been crawled from the following news websites. The aligned documents annotated in the dataset NLPC-UOM/document_alignment_dataset-Sinhala-Tamil-English had been considered to annotate the aligned sentences. | 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 sentences have been manually annotated. ### **Dataset** The folder structure for each news source is as follows. ```python si-en |--army |--Sinhala |--English |--army.si-en |--hiru
|--Sinhala |--English |--hiru.si-en |--itn |--Sinhala |--English |--itn.si-en |--newsfirst |--Sinhala |--English |--newsfirst.si-en ta-en si-ta ``` Sinhala/English/Tamil - contain the aligned documents in the two languages with respect to the news source. (army/hiru/itn/newsfirst) Aligned documents contain the same ID.
army.si-en - golden aligned sentence alignment. Each sentence is referenced according to the languageprefix_fileid_sentenceId.
### **Citation Information** @article{fernando2022exploiting,
title={Exploiting bilingual lexicons to improve multilingual embedding-based document and sentence alignment for low-resource languages},
author={Fernando, Aloka and Ranathunga, Surangika and Sachintha, Dilan and Piyarathna, Lakmali and Rajitha, Charith},
journal={Knowledge and Information Systems},
pages={1--42},
year={2022},
publisher={Springer}
}