FourIE - Information Extraction tool

This is FourIE, a neural information extraction system developed by the Natural Language Processing group at the University of Oregon. FourIE annotates text for entity mentions (names, pronouns, nominals), relations, event triggers and argument roles using the information schema defined in the ACE 2005 dataset. FourIE leverages deep learning and graph convolutional networks to jointly perform four tasks in information extraction, i.e., entity mention detection, relation extraction, event detection and argument role prediction in an end-to-end fashion. Our system achieves the state-of-the-art performance for joint information extraction on ACE 2005.

For more information, please check out our NAACL-HLT 2021 paper: Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks.

Please contact Thien Huu Nguyen at thien@cs.uoregon.edu if you have any questions/suggestions.
This tool works best with Google Chrome

Created by: Minh Van Nguyen Viet Dac Lai, Thien Huu Nguyen
Visualization: BRAT

Quick example

Link to article

Currently support: The New York Times CNN

Text to annotate (English only)