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Using open data to create the Catalan IATE e-dictionary

Authors: Mercè Vàzquez; Antoni Oliver; Elisabeth Casademont;

Using open data to create the Catalan IATE e-dictionary

Abstract

AbstractLinguistic resources available in the form of open data are an essential source of information for creating e-dictionaries, but access to these linguistic resources is still limited. This paper presents a method for maximising use of open access linguistic resources and integrating them into specialised e-dictionaries. The method combines automatic compilation of terminology data with the creation of specialised linguistic corpora to produce a Catalan version of the IATE (InterActive Terminology for Europe) database. The paper presents new methodological advances applied here to the production of terminological e-dictionaries, using open access linguistic resources. We observe that, as a result of this new methodology, the Catalan version of the IATE will be able to include specialised economics, law and health dictionaries. In conclusion, the new methodology presented here permits the creation of new models of specialised e-dictionaries, facilitates the compilation of terminology in any language and unifies the access format for terminology data.

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Keywords

e-dictionaries, terminological dictionaries, lexicography, terminology, open data, natural language processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Top 10%
Green