Question Answer System Deliverable #2

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Presentation transcript:

Question Answer System Deliverable #2 Jonggun Park Haotian He Maria Antoniak Ron Lockwood

System architecture Two modules: Indexing Querying query processing passage retrieval answer processing/ranking

Document Indexing/Retrieval Apache Lucene Two indices Full text (used for idf calculations) Paragraphs (used for scoring results)

Why did Chuck Norris uppercut a horse? Query processing Why did Chuck Norris uppercut a horse? chuck, norris, uppercut, horse Search

Query processing + POS + NER + Chunking + Stemming

Chuck Norris uppercut a horse to make a giraffe

Answer Extraction/Processing Initial solution is a redundancy-based strategy With one big difference Instead of using web queries for snippets We are using results (top 100) from a Lucene query

Answer Extraction Details Input to the Extraction Engine Query word list Stop-word list Focus-word list (e.g. meters, liters, miles, etc.) Passage list – the paragraph results of the query N-gram generation and occurrence counting Filtering out stop words and query words Combining unigram counts with n-gram counts Weighting candidates with idf scores Verifying candidates in documents Lin, J. 2007. An exploration of the principles underlying redundancy-based factoid question answering. Penn Plaza, Suite 701, New York, NY.

D2 Results Strict = 0.01 Lenient = 0.064 Low results… but improvements are coming!

Future work NER Web boosting Query/answer classification

Thank you! Questions?