Graphene: Semantically-Linked Propositions in Open Information Extraction
Matthias Cetto, Christina Niklaus, André Freitas, Siegfried Handschuh
Abstract
We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, together with rhetorical relation identification. In that way, we convert sentences that present a complex linguistic structure into simplified, syntactically sound sentences, from which we can extract propositions that are represented in a two-layered hierarchy in the form of core relational tuples and accompanying contextual information which are semantically linked via rhetorical relations. In a comparative evaluation, we demonstrate that our reference implementation Graphene outperforms state-of-the-art Open IE systems in the construction of correct n-ary predicate-argument structures. Moreover, we show that existing Open IE approaches can benefit from the transformation process of our framework.- Anthology ID:
- C18-1195
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2300–2311
- Language:
- URL:
- https://aclanthology.org/C18-1195
- DOI:
- Cite (ACL):
- Matthias Cetto, Christina Niklaus, André Freitas, and Siegfried Handschuh. 2018. Graphene: Semantically-Linked Propositions in Open Information Extraction. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2300–2311, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Graphene: Semantically-Linked Propositions in Open Information Extraction (Cetto et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/naacl24-info/C18-1195.pdf
- Code
- Lambda-3/Graphene