2017
EMNLP
EMNLP 2017
Revisiting Selectional Preferences for Coreference Resolution
Abstract
AbstractSelectional preferences have long been claimed to be essential for coreference resolution. However, they are modeled only implicitly by current coreference resolvers. We propose a dependency-based embedding model of selectional preferences which allows fine-grained compatibility judgments with high coverage. Incorporating our model improves performance, matching state-of-the-art results of a more complex system. However, it comes with a cost that makes it debatable how worthwhile are such improvements.
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
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Hot Topic Early Bird
- embedding model