@inproceedings{pouran-ben-veyseh-etal-2019-graph,
title = "Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures",
author = "Pouran Ben Veyseh, Amir and
Nguyen, Thien Huu and
Dou, Dejing",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1432",
doi = "10.18653/v1/P19-1432",
pages = "4393--4399",
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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%0 Conference Proceedings
%T Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
%A Pouran Ben Veyseh, Amir
%A Nguyen, Thien Huu
%A Dou, Dejing
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F pouran-ben-veyseh-etal-2019-graph
%X 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.
%R 10.18653/v1/P19-1432
%U https://aclanthology.org/P19-1432
%U https://doi.org/10.18653/v1/P19-1432
%P 4393-4399
Markdown (Informal)
[Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures](https://aclanthology.org/P19-1432) (Pouran Ben Veyseh et al., ACL 2019)
ACL