The devil is in the details: On the pitfalls of event extraction evaluation
Event extraction (EE) is a crucial task aiming at extracting events from texts, which includes
two subtasks: event detection (ED) and event argument extraction (EAE). In this paper, we …
two subtasks: event detection (ED) and event argument extraction (EAE). In this paper, we …
Key news event detection and event context using graphic convolution, clustering, and summarizing methods
Z Liu, Y Zhang, Y Li, Chaomurilige - Applied Sciences, 2023 - mdpi.com
The detection of key events and identification of the events' context have been widely
studied to detect key events from large volumes of online news and identify trends in such …
studied to detect key events from large volumes of online news and identify trends in such …
Type information utilized event detection via multi-channel gnns in electrical power systems
Event detection in power systems aims to identify triggers and event types, which helps
relevant personnel respond to emergencies promptly and facilitates the optimization of …
relevant personnel respond to emergencies promptly and facilitates the optimization of …
Event detection with dual relational graph attention networks
J Mi, P Hu, P Li - … of the 29th International Conference on …, 2022 - aclanthology.org
Event detection, which aims to identify instances of specific event types from pieces of text, is
a fundamental task in information extraction. Most existing approaches leverage syntactic …
a fundamental task in information extraction. Most existing approaches leverage syntactic …
Multi-channels prototype contrastive learning with condition adversarial attacks for few-shot event detection
F Zhang, S Tian, L Yu, Q Yang - Neural Processing Letters, 2024 - Springer
Abstract Few-shot Event Detection (FSED) is a sub-task of Event Detection that aims to
accurately identify event types with limited training instances and enable smooth transfer to …
accurately identify event types with limited training instances and enable smooth transfer to …
Trigger is Non-central: Jointly event extraction via label-aware representations with multi-task learning
Event extraction (EE) occupies an important position in information extraction. Recently,
deep neural network methods have been demonstrated to learn potential features well …
deep neural network methods have been demonstrated to learn potential features well …
Event extraction as machine reading comprehension with question-context bridging
L Liu, M Liu, S Liu, K Ding - Knowledge-Based Systems, 2024 - Elsevier
Most existing methods regard event extraction as the classification task. They not only
heavily rely on named entity recognition, causing error propagation, but are also inefficient …
heavily rely on named entity recognition, causing error propagation, but are also inefficient …
Dependency Structure-Enhanced Graph Attention Networks for Event Detection
Existing models on event detection share three-fold limitations, including (1) insufficient
consideration of the structures between dependency relations,(2) limited exploration of the …
consideration of the structures between dependency relations,(2) limited exploration of the …
面向研究问题的深度学习事件抽取综述
万齐智， 万常选， 胡蓉， 刘德喜， 刘喜平， 廖国琼 - 自动化学报, 2023 - aas.net.cn
事件抽取是一个历史悠久且极具挑战的研究任务, 取得了大量优异的成果. 由于事件抽取涉及的
研究内容较多, 它们的目标和重心各不相同, 使得读者难以全面地了解事件抽取包含的研究任务 …
研究内容较多, 它们的目标和重心各不相同, 使得读者难以全面地了解事件抽取包含的研究任务 …
Improving Cascade Decoding with Syntax-Aware Aggregator and Contrastive Learning for Event Extraction
Cascade decoding framework has shown superior performance on event extraction tasks.
However, it treats a sentence as a sequence and neglects the potential benefits of the …
However, it treats a sentence as a sequence and neglects the potential benefits of the …