@inproceedings{le-nguyen-2021-fine,
title = "Fine-Grained Event Trigger Detection",
author = "Le, Duong and
Nguyen, Thien Huu",
editor = "Merlo, Paola and
Tiedemann, Jorg and
Tsarfaty, Reut",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-main.237",
doi = "10.18653/v1/2021.eacl-main.237",
pages = "2745--2752",
abstract = "Most of the previous work on Event Detection (ED) has only considered the datasets with a small number of event types (i.e., up to 38 types). In this work, we present the first study on fine-grained ED (FED) where the evaluation dataset involves much more fine-grained event types (i.e., 449 types). We propose a novel method to transform the Semcor dataset for Word Sense Disambiguation into a large and high-quality dataset for FED. Extensive evaluation of the current ED methods is conducted to demonstrate the challenges of the generated datasets for FED, calling for more research effort in this area.",
}
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%0 Conference Proceedings
%T Fine-Grained Event Trigger Detection
%A Le, Duong
%A Nguyen, Thien Huu
%Y Merlo, Paola
%Y Tiedemann, Jorg
%Y Tsarfaty, Reut
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F le-nguyen-2021-fine
%X Most of the previous work on Event Detection (ED) has only considered the datasets with a small number of event types (i.e., up to 38 types). In this work, we present the first study on fine-grained ED (FED) where the evaluation dataset involves much more fine-grained event types (i.e., 449 types). We propose a novel method to transform the Semcor dataset for Word Sense Disambiguation into a large and high-quality dataset for FED. Extensive evaluation of the current ED methods is conducted to demonstrate the challenges of the generated datasets for FED, calling for more research effort in this area.
%R 10.18653/v1/2021.eacl-main.237
%U https://aclanthology.org/2021.eacl-main.237
%U https://doi.org/10.18653/v1/2021.eacl-main.237
%P 2745-2752
Markdown (Informal)
[Fine-Grained Event Trigger Detection](https://aclanthology.org/2021.eacl-main.237) (Le & Nguyen, EACL 2021)
ACL
- Duong Le and Thien Huu Nguyen. 2021. Fine-Grained Event Trigger Detection. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 2745–2752, Online. Association for Computational Linguistics.