The structure-mapping engine: algorithm and examples
Artificial Intelligence
WordNet: a lexical database for English
Communications of the ACM
Slot Grammar: A System for Simpler Construction of Practical Natural Language Grammars
Proceedings of the International Symposium on Natural Language and Logic
Textual evidence gathering and analysis
IBM Journal of Research and Development
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The Jeopardy! television quiz show asks natural-language questions and requires natural-language answers. One useful source of information for answering Jeopardy! questions is text from written sources such as encyclopedias or news articles. A text passage may partially or fully indicate that some candidate answer is the correct answer to the question. Recognizing whether it does requires determining the extent to which what the passage is saying about the candidate answer is similar to what the question is saying about the desired answer. This paper describes how structure mapping [1] (an algorithm originally developed for analogical reasoning) is applied to determine similarity between content in questions and passages. That algorithm is one of many used in the Watson question answering system [2]. It contributes a significant amount to Watson's effectiveness.