Summary of the paper

Title Fine-Grained Geographical Relation Extraction from Wikipedia
Authors Andre Blessing and Hinrich Schütze
Abstract In this paper, we present work on enhancing the basic data resource of a context-aware system. Electronic text offers a wealth of information about geospatial data and can be used to improve the completeness and accuracy of geospatial resources (e.g., gazetteers). First, we introduce a supervised approach to extracting geographical relations on a fine-grained level. Second, we present a novel way of using Wikipedia as a corpus based on self-annotation. A self-annotation is an automatically created high-quality annotation that can be used for training and evaluation. Wikipedia contains two types of different context: (i) unstructured text and (ii) structured data: templates (e.g., infoboxes about cities), lists and tables. We use the structured data to annotate the unstructured text. Finally, the extracted fine-grained relations are used to complete gazetteer data. The precision and recall scores of more than 97 percent confirm that a statistical IE pipeline can be used to improve the data quality of community-based resources.
Topics Information Extraction, Information Retrieval, Acquisition, Corpus (creation, annotation, etc.)
Full paper Fine-Grained Geographical Relation Extraction from Wikipedia
Slides Fine-Grained Geographical Relation Extraction from Wikipedia
Bibtex @InProceedings{BLESSING10.519,
  author = {Andre Blessing and Hinrich Schütze},
  title = {Fine-Grained Geographical Relation Extraction from Wikipedia},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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