Question answering system for QA4MRE@CLEF 2012

Pinaki Bhaskar, Partha Pakray, Somnath Banerjee, Samadrita Banerjee, Sivaji Bandyopadhyay, Alexander Gelbukh

Research output: Contribution to journalConference articlepeer-review

20 Scopus citations

Abstract

The article presents the experiments carried out as part of the participation in the main task of QA4MRE@CLEF 2012. In the developed system, we first combine the question and each answer option to form the Hypothesis (H). Stop words are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document using Lucene. Relevant sentences are retrieved from the associated document based on the TF-IDF of the matching query words along with n-gram overlap of the sentence with the H. Each retrieved sentence defines the Text T. Each T-H pair is assigned a ranking score that works on textual entailment principle. A validate weight is automatically assigned to each answer options based on their ranking. A parallel procedure also generates the possible answer patterns from given questions and answer options. Each sentence in the associated document is assigned an inference score with respect to each answer pattern. Evaluated inference score for each answer option is multiplied by the validate weight based on their ranking. The answer option that receives the highest selection score is identified as the most relevant option and selected as the answer to the given question.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1178
StatePublished - 2012
Event2012 Cross Language Evaluation Forum Conference, CLEF 2012 - Rome, Italy
Duration: 17 Sep 201220 Sep 2012

Keywords

  • Named entity
  • QA4MRE data sets
  • Question answering technique
  • Textual entailment

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