Event Extraction (EE) is one of the fundamental tasks in Information
Extraction (IE) that aims to recognize event mentions and their arguments
(i.e., participants) from text. Due to its importance, extensive methods and
resources have been developed for Event Extraction. However, one limitation of
current research for EE involves the under-exploration for non-English
languages in which the lack of high-quality multilingual EE datasets for model
training and evaluation has been the main hindrance. To address this
limitation, we propose a novel Multilingual Event Extraction dataset (MEE) that
provides annotation for more than 50K event mentions in 8 typologically
different languages. MEE comprehensively annotates data for entity mentions,
event triggers and event arguments. We conduct extensive experiments on the
proposed dataset to reveal challenges and opportunities for multilingual EE.

提出了一种新的跨语言的事件抽取数据集，称为 MEE，其中注释了 8 种具有不同语言类型的语言中的 50000 多个实体提及、事件触发和事件参数。在此数据集上进行的实验发现多语言事件抽取的挑战和机遇。