Towards modelling SUMO attributes through WordNet adjectives: a Case Study on Qualities

Itziar Gonzalez-Dios, Javier Alvez, German Rigau


Abstract
Previous studies have shown that the knowledge about attributes and properties in the SUMO ontology and its mapping to WordNet adjectives lacks of an accurate and complete characterization. A proper characterization of this type of knowledge is required to perform formal commonsense reasoning based on the SUMO properties, for instance to distinguish one concept from another based on their properties. In this context, we propose a new semi-automatic approach to model the knowledge about properties and attributes in SUMO by exploiting the information encoded in WordNet adjectives and its mapping to SUMO. To that end, we considered clusters of semantically related groups of WordNet adjectival and nominal synsets. Based on these clusters, we propose a new semi-automatic model for SUMO attributes and their mapping to WordNet, which also includes polarity information. In this paper, as an exploratory approach, we focus on qualities.
Anthology ID:
2020.mmw-1.1
Volume:
Proceedings of the LREC 2020 Workshop on Multimodal Wordnets (MMW2020)
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
LREC | MMW | WS
SIG:
Publisher:
The European Language Resources Association (ELRA)
Note:
Pages:
1–6
Language:
English
URL:
https://www.aclweb.org/anthology/2020.mmw-1.1
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.mmw-1.1.pdf