natural-language-processing-4

Event Extraction

3260 papers • 126 benchmarks • 313 datasets

Determine the extent of the events in a text. Other names: Event Tagging; Event Identification

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in event-extraction-8

Trend

Dataset

Best Model

Actions

ACE2005

GENIA

GENIA 2013

Libraries

i

Use these libraries to find event-extraction-8 models and implementations

Spico197/DocEE

3 papers 222

Datasets

Subtasks

NER Event Causality Identification Zero-shot Event Extraction

Most implemented papers

Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation

Heyan Huang, Xiao Liu, Zhunchen Luo•Sun Sep 23 2018

This paper proposes a novel Jointly Multiple Events Extraction framework to jointly extract multiple event triggers and arguments by introducing syntactic shortcut arcs to enhance information flow and attention-based graph convolution networks to model graph information.

369

Content

Infectious Diseases 2011 (ID)

Cancer Genetics 2013 (CG)

Epigenetics and Post-translational Modifications 2011 (EPI)

Pathway Curation 2013 (PC)

Multi-Level Event Extraction (MLEE)

French Timebank

0

Entity, Relation, and Event Extraction with Contextualized Span Representations

Hannaneh Hajishirzi, Yi Luan, David Wadden, Ulme Wennberg•Sat Sep 07 2019

This work examines the capabilities of a unified, multi-task framework for three information extraction tasks: named entity recognition, relation extraction, and event extraction (called DyGIE++) and achieves state-of-the-art results across all tasks.

656 0

Paper Graph

From POS tagging to dependency parsing for biomedical event extraction

Karin M. Verspoor, Dat Quoc Nguyen•Fri Aug 10 2018

A detailed empirical study comparing traditional feature-based and neural network-based models for POS tagging and dependency parsing in the biomedical context is presented, and the influence of parser selection for a biomedical event extraction downstream task is investigated.

35 0

Paper Graph

Event Extraction by Answering (Almost) Natural Questions

Claire Cardie, Xinya Du•Mon Apr 27 2020

This work introduces a new paradigm for event extraction by formulating it as a question answering (QA) task, which extracts the event arguments in an end-to-end manner and outperforms prior methods substantially.

469 0

Paper Graph

Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction

Jiang Bian, W. Xu, Shun Zheng, Wei Cao•Sun Mar 31 2019

This work proposes a novel end-to-end model, Doc2EDAG, which can generate an entity-based directed acyclic graph to fulfill the document-level EE (DEE) effectively and reformalizes a DEE task with the no-trigger-words design to ease the documents-level event labeling.

192 0

Paper Graph

Giveme5W1H: A Universal System for Extracting Main Events from News Articles

Felix Hamborg, Bela Gipp, Corinna Breitinger•Thu Sep 05 2019

An in-depth description of an improved version of Giveme5W1H, a system that uses syntactic and domain-specific rules to automatically extract the relevant phrases from English news articles to provide answers to 5W 1H questions, which alone can sufficiently summarize the main event reported on in a news article.

49 0

Paper Graph

Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker

Lei Li, Baobao Chang, Tianyu Liu, Runxin Xu•Sun May 30 2021

GIT introduces a Tracker module to track the extracted events and hence capture the interdependency among the events in a document to solve the two challenges of document-level event extraction.

122 0

Paper Graph

Document-level Event Extraction via Parallel Prediction Networks

Kang Liu, Hang Yang, Dianbo Sui, Yubo Chen, Jun Zhao, Taifeng Wang•Thu Dec 31 2020

This paper proposes an end-to-end model, which can extract structured events from a document in a parallel manner, and significantly outperforms current state-of-the-art methods in the challenging DEE task.

96 0

Paper Graph

DEGREE: A Data-Efficient Generation-Based Event Extraction Model

Nanyun Peng, Kai-Wei Chang, I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, Scott Miller, Premkumar Natarajan•Sat Aug 28 2021

DEGREE is proposed, a data-efficient model that formulates event extraction as a conditional generation problem and learns triggers and arguments jointly in an end-to-end manner, which encourages the model to better utilize the shared knowledge and dependencies among them.

207 0

Paper Graph

Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction

Guanghui Qin, Mark Dredze, Benjamin Van Durme, M. Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton W. Murray, Aaron Steven White•Mon Sep 13 2021

This work explores techniques including data projection and self-training, and how different pretrained encoders impact them, and finds that a combination of approaches leads to better performance than any one cross-lingual strategy in particular.

29 0

Paper Graph

Adding a benchmark result helps the community track progress.