Kalyani P. Kamune

Work place: RKNEC, Department of Computer Science, Nagpur, 440013, India

E-mail: kalyanikamune24@gmail.com


Research Interests: Artificial Intelligence, Natural Language Processing, Computer Architecture and Organization


Kalyani P. Kamune, born on 24th March 1991 in Nagpur. She received her Bachelor of Engineering in Computer Technology in 2008. She completed her M.Tech from Computer Science in 2014 from Shri Ramdeo baba College of Engineering and Management, Nagpur, India. Her research areas are Natural Language Processing, and Artificial Intelligence.

Author Articles
Hybrid Approach to Pronominal Anaphora Resolution in English Newspaper Text

By Kalyani P. Kamune Avinash Agrawal

DOI: https://doi.org/10.5815/ijisa.2015.02.08, Pub. Date: 8 Jan. 2015

One of the challenges in natural language understanding is to determine which entities to be referred in the discourse and how they relate to each other. Anaphora resolution needs to be addressed in almost every application dealing with natural language such as language understanding and processing, dialogue system, system for machine translation, discourse modeling, information extraction. This paper represents a system that uses the combination of constraint-based and preferences-based architectures; each uses a different source of knowledge and proves effective on computational and theoretical basis, instead of using a monolithic architecture for anaphora resolution. This system identifies both inter-sentential and intra-sentential antecedents of “Third person pronoun anaphors” and “Pleonastic it”. This system uses Charniak Parser (parser05Aug16) as an associated tool, and it relays on the output generated by it. Salience measures derived from parse tree are used in order to find out accurate antecedents from the list of all potential antecedents. We have tested the system extensively on 'Reuters Newspaper corpus' and efficiency of the system is found to be 81.9%.

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