EventGraph at CASE 2021 Task 1: A General Graph-based Approach to Protest Event Extraction
Huiling You, David Samuel, Samia Touileb, and Lilja {\O}vrelid

TL;DR
This paper introduces EventGraph, a graph-based semantic parser for protest event extraction, demonstrating its effectiveness across multiple languages and achieving competitive rankings in the CASE 2021 shared task.
Contribution
The paper presents a novel graph-based approach for protest event extraction, comparing different graph encodings and showing the superiority of the node-centric method.
Findings
Node-centric graphs outperform labeled-edge graphs.
EventGraph achieves top rankings in English and Portuguese.
The approach is effective across multiple languages.
Abstract
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: https://github.com/huiling-y/eventgraph_at_case
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Software Engineering Research
