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arXiv · 1906.06947

Open Domain Event Extraction Using Neural Latent Variable Models

Xiao Liu·Heyan Huang·Yue Zhang
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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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Xiao Liu, Heyan Huang, Yue Zhang. 2019-06-17. Open Domain Event Extraction Using Neural Latent Variable Models. https://doi.org/10.18653/v1%2Fp19-1276

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