NCSU: Modeling Temporal Relations with Markov Logic and Lexical Ontology

Eun Ha, Alok Baikadi, Carlyle Licata, James C. Lester
2010 International Workshop on Semantic Evaluation  
As a participant in TempEval-2, we address the temporal relations task consisting of four related subtasks. We take a supervised machine-learning technique using Markov Logic in combination with rich lexical relations beyond basic and syntactic features. One of our two submitted systems achieved the highest score for the Task F (66% precision), untied, and the second highest score (63% precision) for the Task C, which tied with three other systems.
dblp:conf/semeval/HaBLL10 fatcat:2dbhg4l3vfgbveeqmrh3bw75hy