Paper: Markov Logic in Natural Language Processing: Theory Algorithms and Applications

ACL ID N10-4002
Title Markov Logic in Natural Language Processing: Theory Algorithms and Applications
Venue Human Language Technologies
Session Tutorial Abstracts
Year 2010
Authors

, pages 3–4, Los Angeles, California, June 2010. c©2010 Association for Computational Linguistics Markov Logic in Natural Language Processing: Theory, Algorithms, and Applications Hoifung Poon, University of Washington Natural languages are characterized by rich relational structures and tight integration with world knowledge. As the field of NLP/CL moves towards more complex and challenging tasks, there has been increasing interest in applying joint inference to leverage such relations and prior knowledge. Recent work in statistical relational learning (a.k.a. structured prediction) has shown that joint inference can not only substantially improve predictive accuracy, but also enable effective learning with little or no labeled information. Markov logic is the unifying framework for st...