Luis Glaser
2020
A Tree Extension for CoNLL-RDF
Christian Chiarcos
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Luis Glaser
Proceedings of the Twelfth Language Resources and Evaluation Conference
The technological bridges between knowledge graphs and natural language processing are of utmost importance for the future development of language technology. CoNLL-RDF is a technology that provides such a bridge for popular one-word-per-line formats as widely used in NLP (e.g., the CoNLL Shared Tasks), annotation (Universal Dependencies, Unimorph), corpus linguistics (Corpus WorkBench, CWB) and digital lexicography (SketchEngine): Every empty-line separated table (usually a sentence) is parsed into an graph, can be freely manipulated and enriched using W3C-standardized RDF technology, and then be serialized back into in a TSV format, RDF or other formats. An important limitation is that CoNLL-RDF provides native support for word-level annotations only. This does include dependency syntax and semantic role annotations, but neither phrase structures nor text structure. We describe the extension of the CoNLL-RDF technology stack for two vocabulary extensions of CoNLL-TSV, the PTB bracket notation used in earlier CoNLL Shared Tasks and the extension with XML markup elements featured by CWB and SketchEngine. In order to represent the necessary extensions of the CoNLL vocabulary in an adequate fashion, we employ the POWLA vocabulary for representing and navigating in tree structures.
Annohub – Annotation Metadata for Linked Data Applications
Frank Abromeit
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Christian Fäth
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Luis Glaser
Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020)
We introduce a new dataset for the Linguistic Linked Open Data (LLOD) cloud that will provide metadata about annotation and language information harvested from annotated language resources like corpora freely available on the internet. To our knowledge annotation metadata is not provided by any metadata provider, e.g. linghub, datahub or CLARIN so far. On the other hand, language metadata that is found on such portals is rarely provided in machine-readable form, especially as Linked Data. In this paper, we describe the harvesting process, content and structure of the new dataset and its application in the Lin|gu|is|tik portal, a research platform for linguists. Aside from that, we introduce tools for the conversion of XML encoded language resources to the CoNLL format. The generated RDF data as well as the XML-converter application are made public under an open license.
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