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Toponym disambiguation in historical documents using network analysis of qualitative relationships

Published: 05 November 2019 Publication History

Abstract

In this paper we use network analysis to identify qualitative "neighbors" for toponyms in an eighteenth-century French encyclopedia, but could apply to any entry-based text with annotated toponyms. This method draws on relations in a corpus of articles, which improves disambiguation at a later stage with an external resource. We suggest the network as an alternative to geospatial representation, a useful proxy when no historical gazetteer exists for the source material's period. Our first experiments have shown that this approach goes beyond a simple text analysis and is able to find relations between toponyms that are not co-occurring in the same documents. Network relations are also usefully compared with disambiguated toponyms to evaluate geographical coverage, and the ways that geographical discourse is expressed, in historical texts.

References

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Mariona Coll Ardanuy and Caroline Sporleder. 2017. Toponym Disambiguation in Historical Documents Using Semantic and Geographic Features. In Proceedings of the 2Nd International Conference on Digital Access to Textual Cultural Heritage (DATeCH2017). ACM, New York, NY, USA, 175--180.
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Carmen Brando, Francesca Frontini, and Jean-Gabriel Ganascia. 2016. REDEN: Named Entity Linking in Digital Literary Editions Using Linked Data Sets. Complex Systems Informatics and Modeling Quarterly 7 (July 2016), 60 -- 80.
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Davide Buscaldi. 2011. Approaches to Disambiguating Toponyms. SIGSPATIAL Special 3, 2 (July 2011), 16--19.
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Jochen L Leidner. 2008. Toponym resolution in text: Annotation, evaluation and applications of spatial grounding of place names. Universal-Publishers.
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Bruno Martins, Ivo Anastácio, and Pável Calado. 2010. A Machine Learning Approach for Resolving Place References in Text. Springer Berlin Heidelberg, Berlin, Heidelberg, 221--236.
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Katherine McDonough, Ludovic Moncla, and Matje van de Camp. 2019. Named entity recognition goes to old regime France: geographic text analysis for early modern French corpora. International Journal of Geographical Information Science 0, 0 (2019), 1--25.
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Ludovic Moncla, Walter Renteria-Agualimpia, Javier Nogueras-Iso, and Mauro Gaio. 2014. Geocoding for Texts with Fine-grain Toponyms: An Experiment on a Geoparsed Hiking Descriptions Corpus. In Proceedings of the 22Nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL '14). ACM, New York, NY, USA, 183--192.
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Gianluca Quercini and Hanan Samet. 2014. Uncovering the Spatial Relatedness in Wikipedia. In Proceedings of the 22Nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL '14). ACM, New York, NY, USA, 153--162.
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João Santos, Ivo Anastácio, and Bruno Martins. 2015. Using machine learning methods for disambiguating place references in textual documents. GeoJournal 80, 3 (01 Jun 2015), 375--392.
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David A. Smith and Gregory Crane. 2001. Disambiguating Geographic Names in a Historical Digital Library. In Research and Advanced Technology for Digital Libraries, Panos Constantopoulos and Ingeborg T. Sølvberg (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 127--136.
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Andreas Spitz, Johanna Geiß, and Michael Gertz. 2016. So Far Away and Yet So Close: Augmenting Toponym Disambiguation and Similarity with Text-based Networks. In Proceedings of the Third International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data (GeoRich '16). ACM, New York, NY, USA, Article 2, 6 pages.

Cited By

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  • (2021)Deep Learning for Toponym Resolution: Geocoding Based on Pairs of ToponymsISPRS International Journal of Geo-Information10.3390/ijgi1012081810:12(818)Online publication date: 2-Dec-2021
  • (2021)Can I believe what I see? Data visualization and trust in the humanitiesInterdisciplinary Science Reviews10.1080/03080188.2021.187287446:4(522-546)Online publication date: 12-Oct-2021
  • (2020)Classification des entités nommées dans l’Encyclopédie ou dictionnaire raisonné des sciences des arts et des métiers par une société de gens de lettres (1751-1772)SHS Web of Conferences10.1051/shsconf/2020781100878(11008)Online publication date: 4-Sep-2020

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cover image ACM Conferences
GeoHumanities '19: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Geospatial Humanities
November 2019
45 pages
ISBN:9781450369602
DOI:10.1145/3356991
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 05 November 2019

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Author Tags

  1. digital humanities
  2. geographic information retrieval
  3. toponym disambiguation

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GeoHumanities '19 Paper Acceptance Rate 6 of 8 submissions, 75%;
Overall Acceptance Rate 15 of 21 submissions, 71%

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Cited By

View all
  • (2021)Deep Learning for Toponym Resolution: Geocoding Based on Pairs of ToponymsISPRS International Journal of Geo-Information10.3390/ijgi1012081810:12(818)Online publication date: 2-Dec-2021
  • (2021)Can I believe what I see? Data visualization and trust in the humanitiesInterdisciplinary Science Reviews10.1080/03080188.2021.187287446:4(522-546)Online publication date: 12-Oct-2021
  • (2020)Classification des entités nommées dans l’Encyclopédie ou dictionnaire raisonné des sciences des arts et des métiers par une société de gens de lettres (1751-1772)SHS Web of Conferences10.1051/shsconf/2020781100878(11008)Online publication date: 4-Sep-2020

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