In this paper we present COCO-EX, a tool for Extracting Concepts from texts and linking them to the ConceptNet knowledge graph. COCO-EX extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph. COCO-EX takes into account the challenging characteristics of ConceptNet, namely that - unlike conventional knowledge graphs - nodes are represented as non-canonicalized, free-form text. This means that i) concepts are not normalized; ii) they often consist of several different, nested phrase types; and iii) many of them are uninformative, over-specific, or misspelled. A commonly used shortcut to circumvent these problems is to apply string matching. We compare COCO-EX to this method and show that COCO-EX enables the extraction of meaningful, important rather than overspecific or uninformative concepts, and allows to assess more relational information stored in the knowledge graph.
CITATION STYLE
Becker, M., Korfhage, K., & Frank, A. (2021). COCO-EX: A tool for linking concepts from texts to conceptnet. In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the System Demonstrations (pp. 119–126). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.eacl-demos.15
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