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

Abstract

Abstract. We present a declarative approach implemented in a comprehensive open-source framework based on DBpedia to extract lexicalsemantic 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.

DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia

“…There are a large number of further crowd-sourced content repositories and DBpedia already had an impact on their structured data publishing and interlinking. Two examples are Wiktionary with the Wiktionary extraction [19] meanwhile becoming part of DBpedia and LinkedGeoData [41], which aims to implement similar data extraction, publishing and linking strategies for OpenStreetMaps.…”

“…The overall number of links pointing to DBpedia from other data sets is 39,007,478 according to the Data Hub. 19 However, those counts are entered by users and may not always be valid and up-to-date.…”

“…Due to its fast changing nature, together with the fragmentation of the project into Wiktionary language editions (WLE) with independent layout rules a, configurable mediator/wrapper approach is taken for its automated transformation into a structured knowledge base. The workflow of this dedicated Wiktionary extractor being part of the Wiktionary2RDF [19] project is as follows: For every WLE to be transformed an XML configuration file is provided as input. This configuration is used by the Wiktionary extractor, invoked by the DBpedia extraction framework, to first generate a schema reflecting the configured page structure (wrapper part).…”

DBnary: Wiktionary as a Lemon-based multilingual lexical resource in RDF

“…Indeed, there is a chance that URIs of lexical senses may change between two versions as word senses may be reordered in the original Wiktionary data. 6 We believe that such changes are rather unfrequent, but we still have to find out a way to cope with them.…”

NLP Data Cleansing Based on Linguistic Ontology Constraints

“…For lemon, the maintainers implemented a Python validator 9 , which enables us to directly compare our efforts to a software validator. For NIF there was an early prototype of RDFUnit that used only manual SPARQL test cases.…”