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Open Domain Event Extraction Using Neural Latent Variable Models

2019-09-18 | |  265 |   53 |   0 0 0
Abstract We consider open domain event extraction, the task of extracting unconstraint types of events from news clusters. A novel latent variable neural model is constructed, which is scalable to very large corpus. A dataset is collected and manually annotated, with task-specific evaluation metrics being designed. Results show that the proposed unsupervised model gives better performance compared to the state-of-the-art method for event schema induction.

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