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Automatic Word problem solving has always posed a great challenge for the NLPcommunity. Usually a word problem is a narrative comprising of a few sentencesand a question is asked about a quantity referred in the sentences. Solvingword problem involves reasoning across sentences, identification of operations,their order, relevant quantities and discarding irrelevant quantities. In thispaper, we present a novel approach for automatic arithmetic word problemsolving. Our approach starts with frame identification. Each frame can eitherbe classified as a state or an action frame. The frame identification isdependent on the verb in a sentence. Every frame is unique and is identified byits slots. The slots are filled using dependency parsed output of a sentence.The slots are entity holder, entity, quantity of the entity, recipient,additional information like place, time. The slots and frames helps to identifythe type of question asked and the entity referred. Action frames act on stateframe(s) which causes a change in quantities of the state frames. The framesare then used to build a graph where any change in quantities can be propagatedto the neighboring nodes. Most of the current solvers can only answer questionsrelated to the quantity, while our system can answer different kinds ofquestions like `who', `what' other than the quantity related questions `howmany'.  There are three major contributions of this paper. 1. Frame Annotated Corpus(with a frame annotation tool) 2. Frame Identification Module 3. A new easilyunderstandable Framework for word problem solving

Arithmetic Word Problem Solver using Frame Identification