抽象的

Automated Anaphora Resolution

Kalyani Kamune, Avinash Agrawal

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 an algorithm that instead of using a monolithic architecture for resolving anaphora, use the combination of 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 intrasentential 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.