Event Argument Extraction

13 papers with code • 2 benchmarks • 2 datasets

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Most implemented papers

HMEAE: Hierarchical Modular Event Argument Extraction

thunlp/HMEAE IJCNLP 2019

Existing event extraction methods classify each argument role independently, ignoring the conceptual correlations between different argument roles.

Event Extraction by Answering (Almost) Natural Questions

xinyadu/eeqa EMNLP 2020

The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments.

Neural Gibbs Sampling for Joint Event Argument Extraction

THU-KEG/NGS 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 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

DebanjanaKar/ArgFuse ACL (CASE) 2021

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

mayubo2333/paie ACL 2022

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 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 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 1 May 2022

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 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.