Shallow Parser for Kannada Sentences using Machine Learning Approach
Prathibha, R J, Padma, M C
International Journal of Computational Linguistics Research, Vol. 8, No. 4, 2017.
DOI: 
Link: http://www.dline.info/jcl/fulltext/v8n4/jclv8n4_2.pdf
Abstract:
Kannada is an inflectional, agglutinative and morphologically rich language. Kannada is a relatively free-word order language but in the phrasal construction it behaves like a fixed word order language. In other words, order of words in Kannada sentence is flexible but in a chunk, order of words is fixed. This paper presents a statistical chunker for Kannada language using conditional random field model. Input for chunker is parts of speech tagged Kannada words. The proposed chunker is trained using Enabling Minority Language Engineering(EMILLE) corpus. The performance of proposed model is tested on stories and novels dataset that are collected from EMILLE corpus. An accuracy of 92.77% and 93.28% is achieved on novels and stories dataset respectively.