Global Intelligent Content: Active Curation of Language Resources using Linked Data

David Lewis, Rob Brennan, Leroy Finn, Dominic Jones, Alan Meehan, Declan O’Sullivan, Sebastian Hellmann, Felix Sasaki


Abstract
As language resources start to become available in linked data formats, it becomes relevant to consider how linked data interoperability can play a role in active language processing workflows as well as for more static language resource publishing. This paper proposes that linked data may have a valuable role to play in tracking the use and generation of language resources in such workflows in order to assess and improve the performance of the language technologies that use the resources, based on feedback from the human involvement typically required within such processes. We refer to this as Active Curation of the language resources, since it is performed systematically over language processing workflows to continuously improve the quality of the resource in specific applications, rather than via dedicated curation steps. We use modern localisation workflows, i.e. assisted by machine translation and text analytics services, to explain how linked data can support such active curation. By referencing how a suitable linked data vocabulary can be assembled by combining existing linked data vocabularies and meta-data from other multilingual content processing annotations and tool exchange standards we aim to demonstrate the relative ease with which active curation can be deployed more broadly.
Anthology ID:
L14-1126
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3546–3549
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1182_Paper.pdf
DOI:
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1182_Paper.pdf