Competitive Self-Trained Pronoun Interpretation

Andrew Kehler, Douglas E. Appelt, Lara Taylor, Aleksandr Simma

Abstract: We 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.