This paper reports on LCC's participation at the Third PASCAL Recognizing Textual Entailment Challenge. First, we summarize our semantic logical-based approach which proved successful in the previous two challenges. Then we highlight this year's innovations which contributed to an overall accuracy of 72.25% for the RTE 3 test data. The novelties include new resources, such as eXtended WordNet KB which provides a large number of world knowledge axioms, event and temporal information provided by the TARSQI toolkit, logic form representations of events, negation, coreference and context, and new improvements of lexical chain axiom generation. Finally, the system's performance and error analysis are discussed.
[1]
Shalom Lappin,et al.
An Algorithm for Pronominal Anaphora Resolution
,
1994,
CL.
[2]
Jerry R. Hobbs.
Resolving pronoun references
,
1986
.
[3]
Dan I. Moldovan,et al.
COGEX at the Second Recognizing Textual Entailment Challenge
,
2006
.
[4]
Roberto Navigli,et al.
Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance
,
2006,
ACL.
[5]
H. Markov,et al.
An algorithm to
,
1997
.
[6]
James Pustejovsky,et al.
Automating Temporal Annotation with TARSQI
,
2005,
ACL.
[7]
Dan I. Moldovan,et al.
Applying COGEX to Recognize Textual Entailment
,
2005,
MLCW.