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.

SWEETpediaAI3:::Adaptive InformationAI3:::Adaptive Information

Plsa/data.txt at master · anthonylife/Plsa · GitHub

Language Models Learn Sentiment and Substance from 11,000 Psychoactive Experiences

PDF) 8th Symposium on Languages, Applications and Technologies, SLATE 2019, June 27-28, 2019, Coimbra, Portugal

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

CryptoPunkets #895 - CryptoPunkets

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

PDF] Building Linguistic Corpora from Wikipedia Articles and Discussions

Gjergji Kasneci - Microsoft Research

PDF] Semantic Full-Text Search with ESTER: Scalable, Easy, Fast

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

PDF] Hypergraph Modelization of a Syntactically Annotated English Wikipedia Dump