A Rule Based Answer Extraction System with Stemming & Anaphora Resolution

Abstract

Natural Language Processing (NLP) is an area of computer Science and Sub area of Artificial Intelligence (AI).
We are developing a rule-based system that can read a large collection of text (say for e.g. story) and find the sentence in the text that best answers the given question. The system uses set of handcrafted rules augmented with some NLP techniques like stemming, named entity extraction etc. that look for Lexical and semantic clues in the question and the text (i.e. story). Each rule awards a certain number of points to each sentence. After all of the rules have been applied, the sentence that obtains the highest score is returned as the answer.