This paper presents our submission to the 2022 edition of the CASE 2021
shared task 1, subtask 4. The EventGraph system adapts an end-to-end,
graph-based semantic parser to the task of Protest Event Extraction and more
specifically subtask 4 on event trigger and argument extraction. We experiment
with various graphs, encoding the events as either "labeled-edge" or
"node-centric" graphs. We show that the "node-centric" approach yields best
results overall, performing well across the three languages of the task, namely
English, Spanish, and Portuguese. EventGraph is ranked 3rd for English and
Portuguese, and 4th for Spanish. Our code is available at:
this https URL

本文介绍了我们参与 CASE 2021 任务 1 子任务 4 的提交。EventGraph 系统使用端到端的基于图形的语义分析器来适应抗议事件提取，并专门针对子任务 4 的事件触发和参数提取。我们尝试使用各种图形将事件编码为 “标记边缘” 或 “节点中心” 的图形。我们展示了 “节点中心” 方法在整个任务的三种语言（英语、西班牙语和葡萄牙语）中表现最佳。EventGraph 在英语和葡萄牙语中排名第三，在西班牙语中排名第四。

基于图数据的抗议事件抽取：CASE2021 任务 1 的 EventGraph 方法

EventGraph at CASE 2021 Task 1: A General Graph-based Approach to Protest Event Extraction

Event extraction involves the detection and extraction of both the event
triggers and corresponding event arguments. Existing systems often decompose
event extraction into multiple subtasks, without considering their possible
interactions. In this paper, we propose EventGraph, a joint framework for event
extraction, which encodes events as graphs. We represent event triggers and
arguments as nodes in a semantic graph. Event extraction therefore becomes a
graph parsing problem, which provides the following advantages: 1) performing
event detection and argument extraction jointly; 2) detecting and extracting
multiple events from a piece of text; and 3) capturing the complicated
interaction between event arguments and triggers. Experimental results on
ACE2005 show that our model is competitive to state-of-the-art systems and has
substantially improved the results on argument extraction. Additionally, we
create two new datasets from ACE2005 where we keep the entire text spans for
event arguments, instead of just the head word(s). Our code and models are
released as open-source.

本文介绍了 EventGraph，一种将事件编码为图形的联合框架，通过将触发事件和参数表示为语义图形中的节点，以此来解决事件提取的问题，并表明该模型在 ACE2005 上达到了和最先进的系统一样的结果，并且在参数提取方面有了显著的改善。