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An Ontology for CoNLL-RDF: Formal Data Structures for TSV Formats in Language Technology Chiarcos, Christian Ionov, Maxim Glaser, Luis Fäth, Christian language technology data models CoNLL-RDF ontology In language technology and language sciences, tab-separated values (TSV) represent a frequently used formalism to represent linguistically annotated natural language, often addressed as "CoNLL formats". A large number of such formats do exist, but although they share a number of common features, they are not interoperable, as different pieces of information are encoded differently in these dialects. CoNLL-RDF refers to a programming library and the associated data model that has been introduced to facilitate processing and transforming such TSV formats in a serialization-independent way. CoNLL-RDF represents CoNLL data, by means of RDF graphs and SPARQL update operations, but so far, without machine-readable semantics, with annotation properties created dynamically on the basis of a user-defined mapping from columns to labels. Current applications of CoNLL-RDF include linking between corpora and dictionaries [Mambrini and Passarotti, 2019] and knowledge graphs [Tamper et al., 2018], syntactic parsing of historical languages [Chiarcos et al., 2018; Chiarcos et al., 2018], the consolidation of syntactic and semantic annotations [Chiarcos and Fäth, 2019], a bridge between RDF corpora and a traditional corpus query language [Ionov et al., 2020], and language contact studies [Chiarcos et al., 2018]. We describe a novel extension of CoNLL-RDF, introducing a formal data model, formalized as an ontology. The ontology is a basis for linking RDF corpora with other Semantic Web resources, but more importantly, its application for transformation between different TSV formats is a major step for providing interoperability between CoNLL formats. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Christian Chiarcos and Maxim Ionov and Luis Glaser and Christian Fäth 2021 Is Part Of OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.LDK.2021.20 urn:nbn:de:0030-drops-145566 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.20 eng https://creativecommons.org/licenses/by/4.0/legalcode