Fine-grained named entity recognition for sinhala

Azeez, R; Ranathunga, S

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dc.contributor.author	Azeez, R
dc.contributor.author	Ranathunga, S
dc.contributor.editor	Weeraddana, C
dc.contributor.editor	Edussooriya, CUS
dc.date.accessioned	2022-08-09T06:38:14Z
dc.date.available	2022-08-09T06:38:14Z
dc.date.issued	2020
dc.identifier.citation	R. Azeez and S. Ranathunga, "Fine-Grained Named Entity Recognition for Sinhala," 2020 Moratuwa Engineering Research Conference (MERCon), 2020, pp. 295-300, doi: 10.1109/MERCon50084.2020.9185296.	en_US
dc.identifier.uri	http://dl.lib.uom.lk/handle/123/18576
dc.description.abstract	For English, Named Entity Recognition (NER) is more or less a solved problem. However, for low-resourced and morphologically rich languages such as Sinhala, minimal research has been done. In this paper, we present a novel fine-grained Named Entity (NE) tag set and an NE annotated Sinhala corpus of 70k word tokens. We trained a custom NER model for Sinhala based on Conditional Random Fields (CRF). Despite the low-resourced setting, this NER model could achieve an micro-averaged F1 score of 84.8.	en_US
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.relation.uri	https://ieeexplore.ieee.org/document/9185296	en_US
dc.subject	named entity recognition	en_US
dc.subject	sinhala	en_US
dc.subject	named entity	en_US
dc.subject	conditional random fields	en_US
dc.title	Fine-grained named entity recognition for sinhala	en_US
dc.type	Conference-Full-text	en_US
dc.identifier.faculty	Engineering	en_US
dc.identifier.department	Engineering Research Unit, University of Moratuwa	en_US
dc.identifier.year	2020	en_US
dc.identifier.conference	Moratuwa Engineering Research Conference 2020	en_US
dc.identifier.place	Moratuwa, Sri Lanka	en_US
dc.identifier.pgnos	pp. 295-300	en_US
dc.identifier.proceeding	Proceedings of Moratuwa Engineering Research Conference 2020	en_US
dc.identifier.email	rameelaa@uom.lk	en_US
dc.identifier.email	surangika@cse.mrt.ac.lk	en_US
dc.identifier.doi	10.1109/MERCon50084.2020.9185296	en_US