TermitUp: Generation and Enrichment of Linked Terminologies

Tracking #: 2693-3907

This paper is currently under review
Authors: 
Patricia Martin-Chozas
Karen Vázquez-Flores
Pablo Calleja
Elena Montiel-Ponsoda
Víctor Rodríguez-Doncel

Responsible editor: 
Guest Editors Advancements in Linguistics Linked Data 2021

Submission type: 
Tool/System Report
Abstract: 
Domain-specific terminologies play a central role in many language technology solutions. Substantial manual effort is still involved in the creation of such resources, and many of them are published in proprietary formats that cannot be easily reused in other applications. Automatic Term Extraction tools help alleviate this cumbersome task. However, their results are usually in the form of plain lists of terms or as unstructured data with limited linguistic information. Initiatives such as the Linguistic Linked Open Data cloud (LLOD) foster the publication of language resources in open structured formats, specifically RDF, and their linking to other resources on the Web of Data. In order to leverage the wealth of linguistic data in the LLOD and speed up the creation of linked terminological resources, we propose TermitUp, a service that generates enriched domain specific terminologies directly from corpora, and publishes them in open and structured formats. TermitUp is composed of five modules performing terminology extraction, terminology post-processing, terminology enrichment, term relation validation and RDF publication. As part of the pipeline implemented by this service, existing resources in the LLOD are linked with the resulting terminologies, contributing in this way to the population of the LLOD cloud. TermitUp has been used in the framework of European projects tackling different fields, such as the legal domain, with promising results. Different alternatives on how to model enriched terminologies are considered –good practices illustrated with examples are proposed.
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Under Review