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Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures

2019/07/07 by Amir Pouran Ben Veyseh, Veyseh, Amir Pouran Ben, Thien Huu Nguyen +3
Computer Science · #Topic Modeling #Text and Document Classification Technologies #Advanced Text Analysis Techniques

paper · pdf · doi:10.48550/arxiv.1907.03227

Abstract

Event factuality prediction (EFP) is the task of assessing the degree to which an event mentioned in a sentence has happened. For this task, both syntactic and semantic information are crucial to identify the important context words. The previous work for EFP has only combined these information in a simple way that cannot fully exploit their coordination. In this work, we introduce a novel graph-based neural network for EFP that can integrate the semantic and syntactic information more effectively. Our experiments demonstrate the advantage of the proposed model for EFP.

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