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Mapping the Past: Geographically Linking an Early 20th Century Swedish Encyclopedia with Wikidata

arXiv 2406.17903 ↗First posted 25 Jun 2024cs.CL cs.DLcited by 0

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Abstract (arXiv)

In this paper, we describe the extraction of all the location entries from a prominent Swedish encyclopedia from the early 20th century, the textitNordisk Familjebok `Nordic Family Book.' We focused on the second edition called textitUggleupplagan, which comprises 38 volumes and over 182,000 articles. This makes it one of the most extensive Swedish encyclopedias. Using a classifier, we first determined the category of the entries. We found that approximately 22 percent of them were locations. We applied a named entity recognition to these entries and we linked them to Wikidata. Wikidata enabled us to extract their precise geographic locations resulting in almost 18,000 valid coordinates. We then analyzed the distribution of these locations and the entry selection process. It showed a higher density within Sweden, Germany, and the United Kingdom. The paper sheds light on the selection and representation of geographic information in the textitNordisk Familjebok, providing insights into historical and societal perspectives. It also paves the way for future investigations into entry selection in different time periods and comparative analyses among various encyclopedias.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 35 references that are in the map. First posted on arXiv 25 Jun 2024.

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References · 9

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  4. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,899
  5. 2019Zero-Shot Entity Linking by Reading Entity Descriptionscited by 124
  6. 2020Playing with Words at the National Library of Sweden -- Making a Swedish BERTcited by 35
  7. 2016Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networkscited by 14
  8. 2022Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problemcited by 11
  9. 2022Connecting a French Dictionary from the Beginning of the 20th Century to Wikidatacited by 4

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