Event Argument Extraction
29 papers with code • 2 benchmarks • 2 datasets
Libraries
Use these libraries to find Event Argument Extraction models and implementations
ACE 2005
WikiEvents
Most implemented papers
Event Extraction by Answering (Almost) Natural Questions
The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments.
HMEAE: Hierarchical Modular Event Argument Extraction
Existing event extraction methods classify each argument role independently, ignoring the conceptual correlations between different argument roles.
Neural Gibbs Sampling for Joint Event Argument Extraction
THU-KEG/NGS
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Asian Chapter of the Association for Computational Linguistics 2020
Existing EAE methods either extract each event argument roles independently or sequentially, which cannot adequately model the joint probability distribution among event arguments and their roles.
Document-Level Event Argument Extraction by Conditional Generation
raspberryice/gen-arg
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NAACL 2021
On the task of argument extraction, we achieve an absolute gain of 7. 6% F1 and 5. 7% F1 over the next best model on the RAMS and WikiEvents datasets respectively.
ArgFuse: A Weakly-Supervised Framework for Document-Level Event Argument Aggregation
Most of the existing information extraction frameworks (Wadden et al., 2019; Veysehet al., 2020) focus on sentence-level tasks and are hardly able to capture the consolidated information from a given document.
Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction
We have conducted extensive experiments on three benchmarks, including both sentence- and document-level EAE.
Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction
pluslabnlp/x-gear
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ACL 2022
We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE).
A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction
pkunlp-icler/tsar
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NAACL 2022
In this paper, we focus on extracting event arguments from an entire document, which mainly faces two critical problems: a) the long-distance dependency between trigger and arguments over sentences; b) the distracting context towards an event in the document.
CUP: Curriculum Learning based Prompt Tuning for Implicit Event Argument Extraction
linmou/cup
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Implicit event argument extraction (EAE) aims to identify arguments that could scatter over the document.
Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning
osainz59/Ask2Transformers
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Findings (NAACL) 2022
In this work we show that entailment is also effective in Event Argument Extraction (EAE), reducing the need of manual annotation to 50% and 20% in ACE and WikiEvents respectively, while achieving the same performance as with full training.
