MERCon - 2016

Permanent URI for this collectionhttp://192.248.9.226/handle/123/14697

Browse

Browsing MERCon - 2016 by Author "Ahamed, AF"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    item: Conference-Full-text
    Ananya - a named-entity-recognition (ner) system for sinhala language
    (IEEE, 2016-04) Manamini, SAPM; Ahamed, AF; Rajapakshe, RAEC; Reemal, GHA; Jayasena, S; Dias, GV; Ranathunga, S; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
    Named-Entity-Recognition (NER) is one of the major tasks under Natural Language Processing, which is widely used in the fields of Computer Science and Computational Linguistics. However, the amount of prior research done on NER for Sinhala is very minimal. In this paper, we present data-driven techniques to detect Named Entities in Sinhala text, with the use of Conditional Random Fields (CRF) and Maximum Entropy (ME) statistical modeling methods. Results obtained from experiments indicate that CRF, which provided the highest accuracy for the same task for other languages outperforms ME in Sinhala NER as well. Furthermore, we identify different linguistic features such as orthographic word level and contextual information that are effective with both CRF and ME Algorithms.