Type nanotheories: a framework for term comparison

We present in this paper Type Nanotheories (TN), a framework for representing the knowledge necessary for performing similarity comparisons between pairs of terms of the same type. TN itself uses another methodology, namely Support Outcomes, which is also introduced. Many IR and NLP applications use redundancy as a factor to increase confidence, and TN-based comparisons can determine redundancy better than simple string comparisons. Results include a showing of a 14% increase in Confidence-Weighted Score for an end-to-end QA system and an up to 68% improvement over baseline in an answer-key equivalencing experiment.

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