EMNLP 2022main10 citations

Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset

Haolin Deng, Yanan Zhang, Yangfan Zhang, Wangyang Ying, Changlong Yu, Jun Gao, Wei Wang, Xiaoling Bai

Abstract

Event extraction (EE) is crucial to downstream tasks such as new aggregation and event knowledge graph construction. Most existing EE datasets manually define fixed event types and design specific schema for each of them, failing to cover diverse events emerging from the online text. Moreover, news titles, an important source of event mentions, have not gained enough attention in current EE research. In this paper, we present Title2Event, a large-scale sentence-level dataset benchmarking Open Event Extraction without restricting event types. Title2Event contains more than 42,000 news titles in 34 topics collected from Chinese web pages. To the best of our knowledge, it is currently the largest manually annotated Chinese dataset for open event extraction. We further conduct experiments on Title2Event with different models and show that the characteristics of titles make it challenging for event extraction, addressing the significance of advanced study on this problem. The dataset and baseline codes are available at https://open-event-hub.github.io/title2event.

BibTeX
@inproceedings{deng-etal-2022-title2event,
    title = "{T}itle2{E}vent: Benchmarking Open Event Extraction with a Large-scale {C}hinese Title Dataset",
    author = "Deng, Haolin  and
      Zhang, Yanan  and
      Zhang, Yangfan  and
      Ying, Wangyang  and
      Yu, Changlong  and
      Gao, Jun  and
      Wang, Wei  and
      Bai, Xiaoling  and
      Yang, Nan  and
      Ma, Jin  and
      Chen, Xiang  and
      Zhou, Tianhua",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.437/",
    doi = "10.18653/v1/2022.emnlp-main.437",
    pages = "6511--6524"
}
Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset · EMNLP 2022