AGRI-QAS question-answering system for agriculture domain

In this paper, we focus on the need for a robust domain specific question answering system targeting agriculture domain. It aims to help farmers get information and resolve their queries related to agriculture and thereby improving agriculture literacy. The system is based on the principles of natural language processing and information retrieval. Most of the currently available information retrieval tools return ranked list of documents instead of precise answers and do not support runtime answer retrieval. Thus we focus on developing a system which processes unstructured data and returns actual answer for FACTOID questions such as `which´, `what´, `who´, `where´. For example, “which diseases affect the wheat crop?”, “what are the prevalent diseases in North-America region?” etc.