### **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 <br/>
      |--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.<br/>
army.si-en - golden aligned sentence alignment. Each sentence is referenced according to the languageprefix_fileid_sentenceId. <br/>


### **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/>
}
task_categories:sentence-similarity task_categories:translation language:si language:ta language:en region:us
{"language": ["si", "ta", "en"], "task_categories": ["sentence-similarity", "translation"]}
TAGS
#task_categories-sentence-similarity #task_categories-translation #language-Sinhala #language-Tamil #language-English #region-us 

### 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.



The aligned sentences have been manually annotated.


### Dataset


The folder structure for each news source is as follows.


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.  

URL-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}  

}



### 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.



The aligned sentences have been manually annotated. ### Dataset


The folder structure for each news source is as follows.


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.  

URL-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}  

}
TAGS
#task_categories-sentence-similarity #task_categories-translation #language-Sinhala #language-Tamil #language-English #region-us 
 ### 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.



The aligned sentences have been manually annotated. ### Dataset


The folder structure for each news source is as follows.


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.  

URL-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}  

}
passage: TAGS
#task_categories-sentence-similarity #task_categories-translation #language-Sinhala #language-Tamil #language-English #region-us 
### 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.



The aligned sentences have been manually annotated.### Dataset


The folder structure for each news source is as follows.


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.  

URL-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}  

}