Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Slot Grammar: A System for Simpler Construction of Practical Natural Language Grammars
Proceedings of the International Symposium on Natural Language and Logic
Splitting complex temporal questions for question answering systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Question answering using constraint satisfaction: QA-by-Dossier-with-Constraints
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Semantic Decomposition for Question Answering
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Special questions and techniques
IBM Journal of Research and Development
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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 decomposition approach by implementing the framework on top of a state-of-the-art QA system, showing a statistically significant improvement over its accuracy.