Graphene: a Context-Preserving Open Information Extraction System

Matthias Cetto, Christina Niklaus, André Freitas, Siegfried Handschuh


Abstract
We introduce Graphene, an Open IE system whose goal is to generate accurate, meaningful and complete propositions that may facilitate a variety of downstream semantic applications. For this purpose, we transform syntactically complex input sentences into clean, compact structures in the form of core facts and accompanying contexts, while identifying the rhetorical relations that hold between them in order to maintain their semantic relationship. In that way, we preserve the context of the relational tuples extracted from a source sentence, generating a novel lightweight semantic representation for Open IE that enhances the expressiveness of the extracted propositions.
Anthology ID:
C18-2021
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Editor:
Dongyan Zhao
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
94–98
Language:
URL:
https://aclanthology.org/C18-2021
DOI:
Bibkey:
Cite (ACL):
Matthias Cetto, Christina Niklaus, André Freitas, and Siegfried Handschuh. 2018. Graphene: a Context-Preserving Open Information Extraction System. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 94–98, Santa Fe, New Mexico. Association for Computational Linguistics.
Cite (Informal):
Graphene: a Context-Preserving Open Information Extraction System (Cetto et al., COLING 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/naacl24-info/C18-2021.pdf
Code
 Lambda-3/Graphene