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Parallel and nested decomposition for factoid questions

  • BRANIMIR BOGURAEV (a1), SIDDHARTH PATWARDHAN (a1), ADITYA KALYANPUR (a1), JENNIFER CHU-CARROLL (a1) and ADAM LALLY (a1)...
Abstract
Abstract

Typically, automatic Question Answering (QA) approaches use the question in its entirety in the search for potential answers. We argue that decomposing complex factoid questions into separate facts about their answers is beneficial to QA, since an answer candidate with support coming from multiple independent facts is more likely to be the correct one. We broadly categorize decomposable questions as parallel or nested, and we present a novel question decomposition framework for enhancing the ability of single-shot QA systems to answer complex factoid questions. Essential to the framework are components for decomposition recognition, question rewriting, and candidate answer synthesis and re-ranking. We discuss the interplay among these, with particular emphasis on decomposition recognition, a process which, we argue, can be sufficiently informed by lexico-syntactic features alone. We validate our approach to decomposition by implementing the framework on top of IBM Watson™, a state-of-the-art QA system, and showing a statistically significant improvement over its accuracy.

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Chu-Carroll J., Brown E., Lally A., and Murdock J. W. 2012a. Identifying implicit relationships. IBM Journal of Research and Development 56 (3.4): 12:110.
Chu-Carroll J., Fan J., Boguraev B., Carmel D., Sheinwald D., and Welty C. 2012b. Finding needles in the haystack: search and candidate generation. IBM Journal of Research and Development 56 (3.4): 6:112.
Chu-Carroll J., Fan J., Schlaefer N., and Zadrozny W. 2012c. Textual resource acquisition and engineering. IBM Journal of Research and Development 56 (3.4): 4:111.
Ferrucci D., Brown E., Chu-Carroll J., Fan J., Gondek D., Kalyanpur A., Lally A., Murdock J. W., Nyberg E., Prager J., Schlaefer N., and Welty C., 2010. Building Watson: an overview of the DeepQA project. AI Magazine 31 (3): 5979.
Gondek D. C., Lally A., Kalyanpur A., Murdock J. W., Duboue P. A., Zhang L., Pan Y., Qiu Z. M., and Welty C. 2012. A framework for merging and ranking of answers in DeepQA. IBM Journal of Research and Development 56 (3.4): 14:1–12.
Hartrumpf S. 2008. Semantic decomposition for question answering. In Proceedings of the 18th European Conference on Artificial Intelligence, pp. 313–7. Amsterdam, Netherlands: IOS Press.
Kalyanpur A., Boguraev B., Patwardhan S., Murdock J. W., Lally A., Welty C., Prager J., Coppola B., Fokoue-Nkoutche A., Zhang L., Pan Y., and Qiu Z. M. 2012a. Structured data and inference in DeepQA. IBM Journal of Research and Development 56 (3.4): 10:114.
Kalyanpur A., Patwardhan S., Boguraev B., Lally A., and Chu-Carroll J. 2011. Fact-based question decomposition for candidate answer re-ranking. In Proceedings of the 20th ACM International Conference on Information and Knowledge Management (CIKM '11), pp. 2045–8. Glasgow, UK: ACM Digital Library.
Kalyanpur A., Patwardhan S., Boguraev B., Lally A., and Chu-Carroll J. 2012b. Fact-based question decomposition in DeepQA. IBM Journal of Research and Development 56 (3.4): 13:111.
Katz B., Borchardt G., and Felshin S. 2005. Syntactic and semantic decomposition strategies for question answering from multiple sources. In Proceedings of the AAAI Workshop on Inference for Textual Question Answering, pp. 3541. Menlo Park, CA: AAAI Press.
Katz B., Lin J., and Quan D. 2002. Natural language annotations for the semantic web. In Proceedings of International Conference on Ontologies, Databases and Applications of Semantics, pp. 1317–31. Berlin, Germany: Springer-Verlag.
Lacatusu F., Hickl A., and Harabagiu S. 2006. The impact of question decomposition on the quality of answer summaries. In Proceedings of the Fifth Language Resources and Evaluation Conference, pp. 1147–52. Genoa, Italy: European Language Resources Association (ELRA).
Lally A., Prager J., McCord M. C., Boguraev B., Patwardhan S., Fan J., Fodor P., and Chu-Carroll J. 2012. Question analysis: how Watson reads a clue. IBM Journal of Research and Development 56 (3.4): 2:114.
Lin C., and Liu R. 2008. An analysis of multi-focus questions. In Proceedings of the SIGIR 2008 Workshop on Focused Retrieval, pp. 30–6. Singapore: ACM.
McCord M. 1989. Slot grammar: a system for simpler construction of practical natural language grammars. In Proceedings of the International Symposium on Natural Language and Logic, pp. 118145. Hamburg, Germany: Springer-Verlag.
McCord M. C., Murdock J. W., and Boguraev B. 2012. Deep parsing in Watson. IBM Journal of Research and Development 56 (3.4): 3:115.
McNemar Q., 1947. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika 12 (2): 153–7.
Murdock J. W., Fan J., Lally A., Shima H., and Boguraev B. 2012a. Textual evidence gathering and analysis. IBM Journal of Research and Development 56 (3.4): 8:114.
Murdock J. W., Kalyanpur A., Welty C., Fan J., Ferrucci D., Gondek D. C., Zhang L., and Kanayama H. 2012b. Typing candidate answers using type coercion. IBM Journal of Research and Development 56 (3.4): 7:113.
Prager J., Brown E., and Chu-Carroll J. 2012. Special questions and techniques. IBM Journal of Research and Development 56 (3.4): 11:113.
Prager J., Chu-Carroll J., and Czuba K. 2004. Question answering by constraint satisfaction: QA-by-dossier with constraints. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, pp. 574–81. Barcelona, Spain: ACL.
Saquete E., Martínez-Barco P., Muñoz R., and Vicedo J. 2004. Splitting complex temporal questions for question answering systems. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, pp. 566–73. Barcelona, Spain: ACL.
Soricut R., and Brill E. 2004. Automatic question answering: beyond the factoid. In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, pp. 5764. Boston, MA: ACL.
Voorhees E. 2002. Overview of the TREC 2002 question answering track. In NIST Special Publication 500-251: The Eleventh Text Retrieval Conference (TREC 2002), pp. 115123. Gaithersburg, MD: Department of Commerce, National Institute of Standards and Technology.
Wang C., Kalyanpur A., Fan J., Boguraev B. K., and Gondek D. C. 2012. Relation extraction and scoring in DeepQA. IBM Journal of Research and Development 56 (3.4): 9:112.
Witten I., and Frank E., 2000. Data Mining – Practical Machine Learning Tools and Techniques with Java Implementations. San Francisco, CA: Morgan-Kaufmann.
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Natural Language Engineering
  • ISSN: 1351-3249
  • EISSN: 1469-8110
  • URL: /core/journals/natural-language-engineering
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