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Documents authored by Marinucci, Ludovica

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Short Paper
DOI: 10.4230/OASIcs.LDK.2019.13
A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data

Authors: Ilkcan Keles, Omar Qawasmeh, Tabea Tietz, Ludovica Marinucci, Roberto Reda, and Marieke van Erp

Published in: OASIcs, Volume 70, 2nd Conference on Language, Data and Knowledge (LDK 2019)

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.
Cite as

Ilkcan Keles, Omar Qawasmeh, Tabea Tietz, Ludovica Marinucci, Roberto Reda, and Marieke van Erp. A Proposal for a Two-Way Journey on Validating Locations in Unstructured and Structured Data. In 2nd Conference on Language, Data and Knowledge (LDK 2019). Open Access Series in Informatics (OASIcs), Volume 70, pp. 13:1-13:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{keles_et_al:OASIcs.LDK.2019.13,
  author =	{Keles, Ilkcan and Qawasmeh, Omar and Tietz, Tabea and Marinucci, Ludovica and Reda, Roberto and van Erp, Marieke},
  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 =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Eskevich, Maria and de Melo, Gerard and F\"{a}th, Christian and McCrae, John P. and Buitelaar, Paul and Chiarcos, Christian and Klimek, Bettina and Dojchinovski, Milan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2019.13},
  URN =		{urn:nbn:de:0030-drops-103778},
  doi =		{10.4230/OASIcs.LDK.2019.13},
  annote =	{Keywords: data validity, natural language processing, linked data}
}
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