Paper: FrameNet-Based Semantic Parsing Using Maximum Entropy Models

ACL ID C04-1179
Title FrameNet-Based Semantic Parsing Using Maximum Entropy Models
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

As part of its description of lexico-semantic predicate frames or conceptual structures, the FrameNet project defines a set of semantic roles specific to the core predicate of a sentence. Recently, researchers have tried to automatically produce semantic interpretations of sentences using this information. Building on prior work, we describe a new method to perform such interpretations. We define sentence segmentation first and show how Maximum Entropy re-ranking helps achieve a level of 76.2% F-score (answer among top- five candidates) or 61.5% (correct answer).