Publikation: GKR : the Graphical Knowledge Representation for semantic parsing
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This paper describes the first version of an open-source semantic parser that creates graphical representations of sentences to be used for further semantic processing, e.g. for natural language inference, reasoning and semantic similarity. The Graphical Knowledge Representation which is output by the parser is inspired by the Abstract Knowledge Representation, which separates out conceptual and contextual levels of representation that deal respectively with the subject matter of a sentence and its existential commitments. Our representation is a layered graph with each subgraph holding different kinds of information, including one sub-graph for concepts and one for contexts. Our first evaluation of the system shows an F-score of 85% in accurately representing sentences as semantic graphs.
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KALOULI, Aikaterini-Lida, Richard CROUCH, 2018. GKR : the Graphical Knowledge Representation for semantic parsing. Workshop on Computational Semantics beyond Events and Roles (SemBEaR 2018). New Orleans, Louisiana, 5. Juni 2018. In: BLANCO, Eduardo, ed., Roser MORANTE, ed.. Proceedings of the Workshop on Computational Semantics beyond Events and Roles (SemBEaR 2018). Stroudsburg, PA: The Association for Computational Linguistics, 2018, pp. 27-37. ISBN 978-1-948087-19-3. Available under: doi: 10.18653/v1/W18-1304BibTex
@inproceedings{Kalouli2018Graph-44106, year={2018}, doi={10.18653/v1/W18-1304}, title={GKR : the Graphical Knowledge Representation for semantic parsing}, isbn={978-1-948087-19-3}, publisher={The Association for Computational Linguistics}, address={Stroudsburg, PA}, booktitle={Proceedings of the Workshop on Computational Semantics beyond Events and Roles (SemBEaR 2018)}, pages={27--37}, editor={Blanco, Eduardo and Morante, Roser}, author={Kalouli, Aikaterini-Lida and Crouch, Richard} }
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