Year: 2007
Type: conference-paper
Abstract: Recent research suggests that sentence structure can improve the accuracy of recognizing textual entailments and paraphrasing. Although background knowledge such as gazetteers, WordNet and custom built knowledge bases are also likely to improve performance, our goal in this paper is to characterize the syntactic features alone that aid in accurate entailment prediction. We describe candidate features, the role of machine learning, and two final decision rules. These rules resulted in an accuracy of 60.50 and 65.87% and average precision of 58.97 and 60.96% in RTE3Test and suggest that sentence structure alone can improve entailment accuracy by 9.25 to 14.62% over the baseline majority class.
Author: Catherine Blake
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2139596890