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An Ontology for CoNLL-RDF: Formal Data Structures for TSV Formats in Language Technology

Authors Christian Chiarcos , Maxim Ionov , Luis Glaser , Christian Fäth

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Author Details

Christian Chiarcos
  • Applied Computational Linguistics Lab, Goethe University Frankfurt, Germany
Maxim Ionov
  • Applied Computational Linguistics Lab, Goethe University Frankfurt, Germany
Luis Glaser
  • Applied Computational Linguistics Lab, Goethe University Frankfurt, Germany
Christian Fäth
  • Applied Computational Linguistics Lab, Goethe University Frankfurt, Germany

Funding

This work was funded by the project "Prêt-à-LLOD" within the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 825182, as well as the project "Linked Open Dictionaries" (LiODi), funded within the eHumanities program of the German Ministry of Education and Science (BMBF, 2015-2021).

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Christian Chiarcos, Maxim Ionov, Luis Glaser, and Christian Fäth. An Ontology for CoNLL-RDF: Formal Data Structures for TSV Formats in Language Technology. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 20:1-20:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/OASIcs.LDK.2021.20

Abstract

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.

Subject Classification

ACM Subject Classification
  • Information systems → Graph-based database models
  • Computing methodologies → Language resources
  • Computing methodologies → Knowledge representation and reasoning
Keywords
  • language technology
  • data models
  • CoNLL-RDF
  • ontology

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References

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