Memorias de investigación
Research Publications in journals:
Multilingual dictionaries and the Web of Data

Research Areas
  • Information technology and adata processing

Nowadays, we are witnessing a growing trend in publishing language resources (lexicons, corpora, dictionaries, etc) as Linked Data (LD) on the Web. LD refers to a set of best practices for exposing, sharing and connecting data on the Web (Bizer et al 2009). In short, the LD paradigm requires that (i) resources are represented on the Web via HTTP URIs (Unique Resource Identifiers), (ii) once a resource is accessed via its URI, information about it is obtained, and (iii) such information contains links to other resources. The basic mechanism to support the representation of resources and their related information is the Resource Description Framework (RDF1), which follows the subject-objectpredicate pattern. Resources can be anything, including documents, people, physical objects and abstract concepts. Following LD principles, a ?Web of Data? emerges in which links are at the level of data, as a counterpart to the ?traditional? Web in which links are established at the level of documents (e.g. hyperlinks between webpages). Publishing language resources as LD offers clear advantages to both the data owners and data users, such as higher independence from domain-specific data formats or vendor-specific APIs, as well as easier access and re-use of linguistic data by semantic-aware software agents. Further, we 1 argue that reaching a critical mass of linguistic data as LD on the Web will set the basis for a new generation of LD-aware Natural Language Processing (NLP) services, with improved scalability and better interoperability level. The latter is, in fact, one of the motivations of LIDER2, a European project that is driving a remarkable community effort in that direction. In this context, the Ontology Engineering Group (OEG3) at Universidad Politécnica de Madrid has started converting a series of bilingual dictionaries and multilingual terminologies and publishing them as LD on the Web. In the following paragraphs we briefly present the RDF conversion process that we have followed, and report on our experience with two of these datasets: Apertium and Terminesp.
Kernerman Dictionary News
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Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial