PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

YAWN, a system to convert the well-known and widely used Wikipedia collection into an XML corpus with semantically rich, self-explaining tags, is presented. The paper presents YAWN, a system to convert the well-known and widely used Wikipedia collection into an XML corpus with semantically rich, self-explaining tags. We introduce algorithms to annotate pages and links with concepts from the WordNet thesaurus. This annotation process exploits categorical information in Wikipedia, which is a high-quality, manually assigned source of information, extracts additional information from lists, and utilizes the invocations of templates with named parameters. We give examples how such annotations can be exploited for high-precision queries.

PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions

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PDF) Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics and Writing: Writing Processes and Authoring Aids}

Debabala Swain Machine Learning and Information 2020, PDF, Artificial Intelligence

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PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

The language network reliably 'tracks' naturalistic meaningful non-verbal stimuli

PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

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PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

PDF) Hypergraph-of-entity