Event Representations with Tensor-based Compositions

Noah Weber; Niranjan Balasubramanian; Nathanael Chambers

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arXiv · 1711.07611

Event Representations with Tensor-based Compositions

Noah Weber·Niranjan Balasubramanian·Nathanael Chambers

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Abstract

Robust and flexible event representations are important to many core areas in language understanding. Scripts were proposed early on as a way of representing sequences of events for such understanding, and has recently attracted renewed attention. However, obtaining effective representations for modeling script-like event sequences is challenging. It requires representations that can capture event-level and scenario-level semantics. We propose a new tensor-based composition method for creating event representations. The method captures more subtle semantic interactions between an event and its entities and yields representations that are effective at multiple event-related tasks. With the continuous representations, we also devise a simple schema generation method which produces better schemas compared to a prior discrete representation based method. Our analysis shows that the tensors capture distinct usages of a predicate even when there are only subtle differences in their surface realizations.

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BibTeX RIS

Noah Weber, Niranjan Balasubramanian, Nathanael Chambers. 2017-11-21. Event Representations with Tensor-based Compositions. https://arxiv.org/abs/1711.07611

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