YAWN: A Semantically Annotated Wikipedia XML Corpus
| dc.contributor.author | Schenkel, Ralf | |
| dc.contributor.author | Suchanek, Fabian | |
| dc.contributor.author | Kasneci, Gjergji | |
| dc.contributor.editor | Kemper, Alfons | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Rose, Thomas | |
| dc.contributor.editor | Jarke, Matthias | |
| dc.contributor.editor | Seidl, Thomas | |
| dc.contributor.editor | Quix, Christoph | |
| dc.contributor.editor | Brochhaus, Christoph | |
| dc.date.accessioned | 2020-02-11T13:22:04Z | |
| dc.date.available | 2020-02-11T13:22:04Z | |
| dc.date.issued | 2007 | |
| dc.description.abstract | 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. | en |
| dc.identifier.isbn | 978-3-88579-197-3 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/31804 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e. V. | |
| dc.relation.ispartof | Datenbanksysteme in Business, Technologie und Web (BTW 2007) – 12. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS) | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-103 | |
| dc.title | YAWN: A Semantically Annotated Wikipedia XML Corpus | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 291 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 277 | |
| gi.conference.date | 07.-09.03.2007 | |
| gi.conference.location | Aachen | |
| gi.conference.sessiontitle | Regular Research Papers |
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