Published:
2020-06-02
Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 34
Volume
Issue:
Vol. 34 No. 09: Issue 9: EAAI-20 / AAAI Special Programs
Track:
Demonstration Track
Downloads:
Abstract:
We present a system which allows a user to create event-event relation extractors on-demand with a small amount of effort. The system provides a suite of algorithms, flexible workflows, and a user interface (UI), to allow rapid customization of event-event relation extractors for new types and domains of interest. Experiments show that it enables users to create extractors for 6 types of causal and temporal relations, with less than 20 minutes of effort per type. Our system (source code, UI) is available at https://github.com/BBN-E/LearnIt. A demonstration video is available at https://vimeo.com/329950144.
DOI:
10.1609/aaai.v34i09.7102
AAAI
Vol. 34 No. 09: Issue 9: EAAI-20 / AAAI Special Programs
ISSN 2374-3468 (Online) ISSN 2159-5399 (Print) ISBN 978-1-57735-835-0 (10 issue set)
Published by AAAI Press, Palo Alto, California USA Copyright © 2020, Association for the Advancement of Artificial Intelligence All Rights Reserved