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.

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PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions

Characterizing the hypergraph-of-entity and the structural impact of its extensions, Applied Network Science

Build a Corpus for NLP Models from Wikipedia dump file, by Yulia Nudelman

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

Publishing Scholarly Editions

PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions

PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus

PDF) Automatic Annotation of Similes in Literary Texts

Topic Modelling (Part 1): Creating Article Corpus from Simple Wikipedia dump

PDF) Overview of the INEX 2010 Question Answering Track (QA@INEX)

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

PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions

Characterizing the hypergraph-of-entity and the structural impact of its extensions, Applied Network Science