| Challenge: | Recent work ignores event-nouns or builds a single model for solving both tasks . however, there are interactions between predicates and event-nons, making it difficult to target only predicate. |
| Approach: | They propose a multi-task learning method that targets event-nouns . their results improve performance of both PASA and ENASA tasks . |
| Outcome: | The proposed model improves both PASA and ENASA tasks compared to a single-task model . it is the first work to employ neural networks in ENASA . |
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Distance-Free Modeling of Multi-Predicate Interactions in End-to-End Japanese Predicate-Argument Structure Analysis (C18-1)
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| Challenge: | Existing models for analyzing PASs in Japanese are lacking in identifying elliptical arguments. |
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Multi-Sentence Argument Linking (2020.acl-main)
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| Challenge: | Existing datasets for cross-sentence linking are small, resulting in a lack of a model for argument linking. |
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Cross-lingual Structure Transfer for Relation and Event Extraction (D19-1)
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Beyond Single-Event Extraction: Towards Efficient Document-Level Multi-Event Argument Extraction (2024.findings-acl)
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Wanlong Liu, Li Zhou, DingYi Zeng, Yichen Xiao, Shaohuan Cheng, Chen Zhang, Grandee Lee, Malu Zhang, Wenyu Chen
| Challenge: | mainstream event argument extraction methods process each event in isolation, resulting in inefficient inference and ignoring correlations among multiple events. |
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Entity-Centric Joint Modeling of Japanese Coreference Resolution and Predicate Argument Structure Analysis (P18-1)
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| Challenge: | Existing methods for predicate argument structure analysis are difficult and difficult . a Japanese model can detect a zero pronoun and identify a referent of the zero pronominator . |
| Approach: | They propose a model that performs coreference resolution and predicate argument structure analysis simultaneously. |
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Neural Adversarial Training for Semi-supervised Japanese Predicate-argument Structure Analysis (P18-1)
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| Challenge: | Japanese predicate-argument structure analysis involves zero anaphora resolution . state-of-the-art models for PAS analysis achieve an accuracy of around 50% for zero pronouns . |
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A Two-Step Approach for Implicit Event Argument Detection (2020.acl-main)
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| Challenge: | et al., 2015) only consider local arguments in the same sentence of the event trigger. |
| Approach: | They propose to decompose the implicit event argument detection task into two sub-problems . they propose to use argument head-word detection and head-to-span expansion to reduce the number of candidates. |
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