Competitive Self-Trained Pronoun Interpretation
by Kehler, A., Appelt, D. E., Taylor L., Simma, A
in Proceedings of the Human Language Technology Conference pp. 33-36,
Organization: North American Chapter of the Association for Computational LinguisticsWe describe a system for pronoun interpretation that is self-trained from raw data, that is, using no annotated training data. The result outperforms a Hobbsian baseline algorithm and is only marginally inferior to an essentially identical, state-of-the-art supervised model trained from a substantial manually-annotated coreference corpus.
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Leveraging Minimal Training Data to Improve Information Extraction Performance |
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Appelt, Doug E | Alumnus |  |
