Leveraging the Crowdsourcing of Lexical Resources for Bootstrapping a Linguistic Data Cloud

We present a declarative approach implemented in a comprehensive open-source framework based on

DBpedia

to extract lexical-semantic resources – an ontology about language use – from

Wiktionary

. The data currently includes language, part of speech, senses, definitions, synonyms, translations and taxonomies (hyponyms, hyperonyms, synonyms, antonyms) for each lexical word. Main focus is on flexibility to the loose schema and configurability towards differing language-editions of

Wiktionary

. This is achieved by a declarative mediator/wrapper approach. The goal is to allow the addition of languages just by configuration without the need of programming, thus enabling the swift and resource-conserving adaption of wrappers by domain experts. The extracted data is as fine granular as the source data in

Wiktionary

and additionally follows the

lemon

model. It enables use cases like disambiguation or machine translation. By offering a linked data service, we hope to extend DBpedia’s central role in the LOD infrastructure to the world of Open Linguistics.