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A Proposal for a Two-way Journey on Validating Locations in Unstructured and Structured Data: Unterschied zwischen den Versionen

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{{Publikation Details
 
|Abstract=The Web of Data has grown explosively over the past few years, and as with any dataset, thereare bound to be invalid statements in the data, as well as gaps. Natural Language Processing(NLP) is gaining interest to fill gaps in data by transforming (unstructured) text into structureddata. However, there is currently a fundamental mismatch in approaches between Linked Dataand NLP as the latter is often based on statistical methods, and the former on explicitly modellingknowledge. However, these fields can strengthen each other by joining forces. In this position paper,we argue that using linked data to validate the output of an NLP system, and using textual data tovalidate Linked Open Data (LOD) cloud statements is a promising research avenue. We illustrateour proposal with a proof of concept on a corpus of historical travel stories
 
|Abstract=The Web of Data has grown explosively over the past few years, and as with any dataset, thereare bound to be invalid statements in the data, as well as gaps. Natural Language Processing(NLP) is gaining interest to fill gaps in data by transforming (unstructured) text into structureddata. However, there is currently a fundamental mismatch in approaches between Linked Dataand NLP as the latter is often based on statistical methods, and the former on explicitly modellingknowledge. However, these fields can strengthen each other by joining forces. In this position paper,we argue that using linked data to validate the output of an NLP system, and using textual data tovalidate Linked Open Data (LOD) cloud statements is a promising research avenue. We illustrateour proposal with a proof of concept on a corpus of historical travel stories
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|Download=OASIcs-LDK-2019-13.pdf
 
|Link=https://drops.dagstuhl.de/opus/frontdoor.php?source_opus=10377
 
|Link=https://drops.dagstuhl.de/opus/frontdoor.php?source_opus=10377
 
|DOI Name=10.4230/OASIcs.LDK.2019.13
 
|DOI Name=10.4230/OASIcs.LDK.2019.13
 
|Forschungsgruppe=Information Service Engineering
 
|Forschungsgruppe=Information Service Engineering
 
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Aktuelle Version vom 17. November 2022, 12:50 Uhr


A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data


A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data



Published: 2019 Mai

Buchtitel: Proc. of the 2nd Conference on Language, Data and Knowledge, Research Track Position Paper (LDK 2019)
Ausgabe: 70
Verlag: OASIcs

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BibTeX

Kurzfassung
The Web of Data has grown explosively over the past few years, and as with any dataset, thereare bound to be invalid statements in the data, as well as gaps. Natural Language Processing(NLP) is gaining interest to fill gaps in data by transforming (unstructured) text into structureddata. However, there is currently a fundamental mismatch in approaches between Linked Dataand NLP as the latter is often based on statistical methods, and the former on explicitly modellingknowledge. However, these fields can strengthen each other by joining forces. In this position paper,we argue that using linked data to validate the output of an NLP system, and using textual data tovalidate Linked Open Data (LOD) cloud statements is a promising research avenue. We illustrateour proposal with a proof of concept on a corpus of historical travel stories

Download: Media:OASIcs-LDK-2019-13.pdf
Weitere Informationen unter: Link
DOI Link: 10.4230/OASIcs.LDK.2019.13



Forschungsgruppe

Information Service Engineering


Forschungsgebiet