Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH scholarly article en Keles, Ilkcan; Qawasmeh, Omar; Tietz, Tabea; Marinucci, Ludovica; Reda, Roberto; van Erp, Marieke https://www.dagstuhl.de/oasics License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
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URN: urn:nbn:de:0030-drops-103778
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A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data

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Abstract

The Web of Data has grown explosively over the past few years, and as with any dataset, there are 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 structured data. However, there is currently a fundamental mismatch in approaches between Linked Data and NLP as the latter is often based on statistical methods, and the former on explicitly modelling knowledge. 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 to validate Linked Open Data (LOD) cloud statements is a promising research avenue. We illustrate our proposal with a proof of concept on a corpus of historical travel stories.

BibTeX - Entry

@InProceedings{keles_et_al:OASIcs:2019:10377,
  author =	{Ilkcan Keles and Omar Qawasmeh and Tabea Tietz and Ludovica Marinucci and Roberto Reda and Marieke van Erp},
  title =	{{A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data}},
  booktitle =	{2nd Conference on Language, Data and Knowledge (LDK 2019)},
  pages =	{13:1--13:8},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Maria Eskevich and Gerard de Melo and Christian F{\"a}th and John P. McCrae and Paul Buitelaar and Christian Chiarcos and Bettina Klimek and Milan Dojchinovski},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/10377},
  URN =		{urn:nbn:de:0030-drops-103778},
  doi =		{10.4230/OASIcs.LDK.2019.13},
  annote =	{Keywords: data validity, natural language processing, linked data}
}

Keywords: data validity, natural language processing, linked data
Seminar: 2nd Conference on Language, Data and Knowledge (LDK 2019)
Issue date: 2019
Date of publication: 16.05.2019


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