Question Answering.ppt

Question Answering Zhikun Meng Overview What is Question Answering? Why Question Answering? How Question Answering? What is the current status of Question Answering? How to evaluate Question Answering? What is the future of Question Answering? What is Question Answering? What is Question Answering? Answer: Question answering systems are designed to find answers to open domain questions in a large collection of documents. Why Question Answering? How Question Answering? General architecture Question Classification e.g. “How much could you rent a Volkswagen bug for in 1966?” Key word preprocessing (split/spell check/normalize) Volkswagen-Volkswagen; “Rotary engine cars were made by what company?” - “What company were rotary engine cars made by?” Question Classification 2. Construction of question representation How much: Question stem rent: Answer type term 1966:Data constraint Volkswagen bug Question Classification 3.Derivation of answer type “How much”+ “rent” -Money Question Classification 4.Key word selection Volkswagen AND bug AND rent Question Classification 5.Key word expansion rent-rented Information Retrieval Retrieval documents and passages: query: Volkswagen AND bug AND rent The retrieval engine returns the documents containing all keywords (e.g.60 document passages from 1,000,000 documents collection) Information Retrieval 2. Passage filtering date constraint 1966. Out of the 60 passages returned by the retrieval engine for Q013, two passages are retained after passage post filtering. Answer Extraction Identification of candidate answers Answer type: Money Identified candidates include $1 and USD 520. Answer Extraction 2. Answer Ranking score: $1 USD 520 Answer Extraction 3. Answer formulation rent a Volkswagen bug for $1 a day What is the current status of Question Answering? Text REtrieval Conference (TREC) / Cross Language Evaluation Forum (CLEF) r.it/ NII-NACSIS Test Collection for IR Systems Project (NTCIR)