Paper: Efficient Search for Transformation-based Inference

ACL ID P12-1030
Title Efficient Search for Transformation-based Inference
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

This paper addresses the search problem in textual inference, where systems need to infer one piece of text from another. A prominent approach to this task is attempts to transform one text into the other through a sequence of inference-preserving transformations, a.k.a. a proof, while estimating the proof?s valid- ity. This raises a search challenge of find- ing the best possible proof. We explore this challenge through a comprehensive investi- gation of prominent search algorithms and propose two novel algorithmic components specifically designed for textual inference: a gradient-style evaluation function, and a local- lookahead node expansion method. Evalua- tions, using the open-source system, BIUTEE, show the contribution of these ideas to search efficiency and proof quality.