Paper: Abductive Reasoning with a Large Knowledge Base for Discourse Processing

ACL ID W11-0124
Title Abductive Reasoning with a Large Knowledge Base for Discourse Processing
Venue IWCS
Session Main Conference
Year 2011
Authors

This paper presents a discourse processing framework based on weighted abduction. We elabo- rate on ideas described in Hobbs et al. (1993) and implement the abductive inference procedure in a system called Mini-TACITUS. Particular attention is paid to constructing a large and reliable knowl- edge base for supporting inferences. For this purpose we exploit such lexical-semantic resources as WordNet and FrameNet. We test the proposed procedure and the obtained knowledge base on the Recognizing Textual Entailment task using the data sets from the RTE-2 challenge for evaluation. In addition, we provide an evaluation of the semantic role labeling produced by the system taking the Frame-Annotated Corpus for Textual Entailment as a gold standard.