OASIcs.LDK.2019.23.pdf
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Automatic Detection of Language and Annotation Model Information in CoNLL Corpora
Authors
Frank Abromeit 
,
Christian Chiarcos
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Volume:
2nd Conference on Language, Data and Knowledge (LDK 2019)
Series: Open Access Series in Informatics (OASIcs)
Conference: Conference on Language, Data and Knowledge (LDK) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2019-05-16
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Frank Abromeit and Christian Chiarcos. Automatic Detection of Language and Annotation Model Information in CoNLL Corpora. In 2nd Conference on Language, Data and Knowledge (LDK 2019). Open Access Series in Informatics (OASIcs), Volume 70, pp. 23:1-23:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/OASIcs.LDK.2019.23
Abstract
We introduce AnnoHub, an on-going effort to automatically complement existing language resources with metadata about the languages they cover and the annotation schemes (tagsets) that they apply, to provide a web interface for their curation and evaluation by means of domain experts, and to publish them as a RDF dataset and as part of the (Linguistic) Linked Open Data (LLOD) cloud. In this paper, we focus on tabular formats with tab-separated values (TSV), a de-facto standard for annotated corpora as popularized as part of the CoNLL Shared Tasks. By extension, other formats for which a converter to CoNLL and/or TSV formats does exist, can be processed analoguously. We describe our implementation and its evaluation against a sample of 93 corpora from the Universal Dependencies, v.2.3.
Subject Classification
ACM Subject Classification
- Information systems → Structure and multilingual text search
Keywords
- LLOD
- CoNLL
- OLiA
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References
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