PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus
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Descrição
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] YAWN: A Semantically Annotated Wikipedia XML Corpus](https://d3i71xaburhd42.cloudfront.net/504c4850b48ae03f9669b100ba9a32a5f6297dcd/3-Table1-1.png)
PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions
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SWEETpediaAI3:::Adaptive InformationAI3:::Adaptive Information
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PDF) Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics and Writing: Writing Processes and Authoring Aids}
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Neural Networks, Machine Learning, and Image Processing, PDF, Skin
![PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus](https://d3i71xaburhd42.cloudfront.net/504c4850b48ae03f9669b100ba9a32a5f6297dcd/4-Figure1-1.png)
PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions
![PDF] YAWN: A Semantically Annotated Wikipedia XML Corpus](https://d3i71xaburhd42.cloudfront.net/c48c5fc5bdb124ff82e00b9386f6b323472a751b/4-Table2-1.png)
PDF] Hypergraph Modelization of a Syntactically Annotated English Wikipedia Dump
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Information, Free Full-Text
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Characterizing the hypergraph-of-entity and the structural impact of its extensions, Applied Network Science
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PDF) University of Amsterdam Data Centric Ad Hoc and Faceted Search Runs
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PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions
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PDF] Semantic Full-Text Search with ESTER: Scalable, Easy, Fast
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The language network reliably 'tracks' naturalistic meaningful non-verbal stimuli
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