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2022 EMNLP EMNLP 2022

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

Abstract

AbstractThis 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Data Science & Analytics and Natural Language Processing

Authors

Huiling You, David Samuel, Samia Touileb, Lilja Øvrelid

Topics

Deep Learning > Architectures > Graph Neural Networks Natural Language Processing > Applications > Information Extraction Data Science & Analytics > Applications > Clustering Machine Learning > Core Methods > Graph Neural Networks Artificial Intelligence > Core AI > Knowledge Graph

Keywords

multilingual nlp argument extraction semantic parsing event extraction semantic parser graph-based parsing graph-based parser event trigger extraction protest event protest event detection node-centric graph graph-based semantic parser

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