Hybrid Model of Automated Anaphora Resolution - Kalyani Pradiprao Kamune; Avinash Agrawal (IAES International Journal of Artificial Intelligence (IJ-AI), 2014)
Anaphora resolution has proven to be a very difficult problem of natural language processing, and it is useful in discourse analysis, language understanding and processing, information exaction, machine translation and many more. This paper represents a system that instead of using a monolithic architecture for resolving anaphora, use the hybrid model which combines the constraint-based and preferences-based architectures, each uses a different source of knowledge, and proves effective on theoretical and computational basis. An algorithm identifies both inter-sentential and intra-sentential antecedents of “Third person pronoun anaphors”, “Pleonastic it”, and “Lexical noun phrase anaphora”. The algorithm use Charniak parser (parser05Aug16) as an associated tool, and it relays on the output generated by it. Salience measures derived from parse tree, in order to find out accurate antecedents from the list of potential antecedents. We have tested the system extensively on 'Reuters Newspaper corpus'.