The (Non)Utility of Predicate-Argument Frequencies for Pronoun Interpretation
by Kehler, A., Appelt, D. E., Taylor L., Simma, A
in Proceedings of the Human Language Technology Conference pp. 289-296,
Address: Boston, MAState-of-the-art pronoun interpretation systems rely predominantly on morphosyntactic contextual features. While the use of deep knowledge and inference to improve these models would appear technically infeasible, previous work has suggested that predicate-argument statistics mined from naturally-occurring data could provide a useful approximation to such knowledge. We test this idea in several system configurations, and conclude from our results and subsequent error analysis that such statistics offer little or no predictive information above that provided by morphosyntax.
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Leveraging Minimal Training Data to Improve Information Extraction Performance |
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Appelt, Doug E | Alumnus |
