Modeling Factual Claims with Semantic Frames

Fatma Arslan, Josue Caraballo, Damian Jimenez, Chengkai Li


Abstract
In this paper, we introduce an extension of the Berkeley FrameNet for the structured and semantic modeling of factual claims. Modeling is a robust tool that can be leveraged in many different tasks such as matching claims to existing fact-checks and translating claims to structured queries. Our work introduces 11 new manually crafted frames along with 9 existing FrameNet frames, all of which have been selected with fact-checking in mind. Along with these frames, we are also providing 2,540 fully annotated sentences, which can be used to understand how these frames are intended to work and to train machine learning models. Finally, we are also releasing our annotation tool to facilitate other researchers to make their own local extensions to FrameNet.
Anthology ID:
2020.lrec-1.306
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2511–2520
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.306
DOI:
Bibkey:
Cite (ACL):
Fatma Arslan, Josue Caraballo, Damian Jimenez, and Chengkai Li. 2020. Modeling Factual Claims with Semantic Frames. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2511–2520, Marseille, France. European Language Resources Association.
Cite (Informal):
Modeling Factual Claims with Semantic Frames (Arslan et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.306.pdf