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- W2952783247 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." @default.
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- W2952783247 date "2019-06-17" @default.
- W2952783247 modified "2023-09-27" @default.
- W2952783247 title "Open Domain Event Extraction Using Neural Latent Variable Models" @default.
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