@inproceedings{witte-etal-2010-flexible,
title = "Flexible Ontology Population from Text: The {O}wl{E}xporter",
author = "Witte, Ren{\'e} and
Khamis, Ninus and
Rilling, Juergen",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/932_Paper.pdf",
abstract = "Ontology population from text is becoming increasingly important for NLP applications. Ontologies in OWL format provide for a standardized means of modeling, querying, and reasoning over large knowledge bases. Populated from natural language texts, they offer significant advantages over traditional export formats, such as plain XML. The development of text analysis systems has been greatly facilitated by modern NLP frameworks, such as the General Architecture for Text Engineering (GATE). However, ontology population is not currently supported by a standard component. We developed a GATE resource called the OwlExporter that allows to easily map existing NLP analysis pipelines to OWL ontologies, thereby allowing language engineers to create ontology population systems without requiring extensive knowledge of ontology APIs. A particular feature of our approach is the concurrent population and linking of a domainand NLP-ontology, including NLP-specific features such as safe reasoning over coreference chains.",
}
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<abstract>Ontology population from text is becoming increasingly important for NLP applications. Ontologies in OWL format provide for a standardized means of modeling, querying, and reasoning over large knowledge bases. Populated from natural language texts, they offer significant advantages over traditional export formats, such as plain XML. The development of text analysis systems has been greatly facilitated by modern NLP frameworks, such as the General Architecture for Text Engineering (GATE). However, ontology population is not currently supported by a standard component. We developed a GATE resource called the OwlExporter that allows to easily map existing NLP analysis pipelines to OWL ontologies, thereby allowing language engineers to create ontology population systems without requiring extensive knowledge of ontology APIs. A particular feature of our approach is the concurrent population and linking of a domainand NLP-ontology, including NLP-specific features such as safe reasoning over coreference chains.</abstract>
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%0 Conference Proceedings
%T Flexible Ontology Population from Text: The OwlExporter
%A Witte, René
%A Khamis, Ninus
%A Rilling, Juergen
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F witte-etal-2010-flexible
%X Ontology population from text is becoming increasingly important for NLP applications. Ontologies in OWL format provide for a standardized means of modeling, querying, and reasoning over large knowledge bases. Populated from natural language texts, they offer significant advantages over traditional export formats, such as plain XML. The development of text analysis systems has been greatly facilitated by modern NLP frameworks, such as the General Architecture for Text Engineering (GATE). However, ontology population is not currently supported by a standard component. We developed a GATE resource called the OwlExporter that allows to easily map existing NLP analysis pipelines to OWL ontologies, thereby allowing language engineers to create ontology population systems without requiring extensive knowledge of ontology APIs. A particular feature of our approach is the concurrent population and linking of a domainand NLP-ontology, including NLP-specific features such as safe reasoning over coreference chains.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/932_Paper.pdf
Markdown (Informal)
[Flexible Ontology Population from Text: The OwlExporter](http://www.lrec-conf.org/proceedings/lrec2010/pdf/932_Paper.pdf) (Witte et al., LREC 2010)
ACL
- René Witte, Ninus Khamis, and Juergen Rilling. 2010. Flexible Ontology Population from Text: The OwlExporter. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).