Abstract
An OWL ontology is used to model a grammar that accounts for subcategorization, showing that ontologies are able to generate (mildly) context-sensitive languages. Semantic Web knowledge representation methods offer a useful way to model the implicit knowledge that defines human linguistic abilities. When a grammar is modeled as a set of ontological constraints (i.e. classes with restrictions on their properties), ungrammatical sentences are defined as facts that lead to inconsistencies which can be discovered by a reasoner. Property chains are used to “pass on” the category of a syntactic complement as the value of a head’s subcategorization feature, modeling the concept of structure sharing that is central to constraint-based theories of syntax like HPSG. By treating utterances as instances and syntactic constraints as axioms, this approach offers points of contact with efforts to model grammars as Linguistic Linked Open Data in the Semantic Web.
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Notes
- 1.
As instances, constituents need to be given unique identifiers, like “Mocked_Hook”, and not generic class names like VP.
- 2.
This is similar to the use of syntactic frames in LexInfo [8].
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- 4.
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Aranovich, R. (2023). Modeling Grammars with Knowledge Representation Methods: Subcategorization as a Test Case. In: Pesquita, C., et al. The Semantic Web: ESWC 2023 Satellite Events. ESWC 2023. Lecture Notes in Computer Science, vol 13998. Springer, Cham. https://doi.org/10.1007/978-3-031-43458-7_21
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