GeoExT 2024
Geographic Information Extraction from Texts 2024

Table of Contents

Summary: There were 14 papers submitted for peer-review to this workshop. Out of these, 12 papers were accepted for this volume, 8 as regular papers and 4 as short papers.

• Preface
  Xuke Hu, Ross Purves, Ludovic Moncla, Jens Kersten, Kristin Stock
• GeoEDdA: A Gold Standard Dataset for Geo-semantic Annotation of Diderot & d'Alembert's Encyclopédie 1-10
  Ludovic Moncla, Denis Vigier, Katherine McDonough
• Geolocation Extraction From Reddit Text Data 11-20
  Mila Stillman, Anna Kruspe
• Detecting Entity Descriptions from Chinese Historical Texts 21-24
  Ye Xia, Bin Wang, Linxuan Yu, Xiaoci Lin, Hui Li
• Towards a Scalable Geoparsing Approach for the Web 25-33
  Sheikh Mastura Farzana, Tobias Hecking
• Where is the News? Improving Toponym Identification and Differentiation in Online News 34-42
  Joseph Shingleton, Ana Basiri
• Fine-Tuning Transformers for Toponym Resolution: A Contextual Embedding Approach to Candidate Ranking 43-51
  Diego Gomes, Ross S. Purves, Michele Volpi
• Enhancing Toponym Resolution with Fine-Tuned LLMs (Llama2) 52-56
  Xuke Hu, Jens Kersten
• Evidence for Systematic Bias in the Spatial Memory of Large Language Models 57-62
  Nir Fulman, Abdulkadir Memduhoğlu, Alexander Zipf
• Exploring Spatial Representations in the Historical Lake District Texts with LLM-based Relation Extraction 63-73
  Erum Haris, Anthony G. Cohn, John G. Stell
• Mapping Global Protest Tendencies: Geolocating Trends and Topics Through Wikipedia Analysis 74-78
  Jiyun Beak, Ludovic Moncla
• The Semantics of Generic Terms in Toponyms: Formal Semantics Meets Multi-source Big Data 79-90
  Giuseppe Samo, Francesco-Alessio Ursini
• Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text? 91-105
  Ilya Ilyankou, Aldo Lipani, Stefano Cavazzi, Xiaowei Gao, James Haworth