Abstract

In this paper, we describe Docforia, a multilayer document model and application programming interface (API) to store formatting, lexical, syntactic, and semantic annotations on Wikipedia and other kinds of text and visualize them. While Wikipedia has become a major NLP resource, its scale and heterogeneity makes it relatively difficult to do experimentations on the whole corpus. These experimentations are rendered even more complexas,to the best of our knowledge,there is no available tool to visualize easily the results of a processing pipeline. We designed Docforia so that it can store millions of documents and billions of tokens, annotated using different processing tools,that themselves use multiple formats, and compatible with cluster computing frameworks such as Hadoop or Spark. The annotation output, either partial or complete, can then be shared more easily. To validate Docforia, we processed six language versions of Wikipedia: English, French, German, Spanish, Russian, and Swedish, up to semantic role labeling, depending on the NLP tools available for a given language. We stored the results in our document model and we created a visualization tool to inspect the annotation results.
Original languageEnglish
Title of host publicationProceedings of the 21st Nordic Conference of Computational Linguistics
PublisherLinköping University Electronic Press
Publication statusPublished - 2017
Event21st Nordic Conference of Computational Linguistics - Wallenberg Conference Center , Gothenburg, Sweden
Duration: 2017 May 232017 May 24

Publication series

NameLinköping Electronic Conference Proceedings
PublisherLinköping University Electronic Press
Volume131
ISSN (Print)1650-3686
ISSN (Electronic)1650-3740

Conference

Conference21st Nordic Conference of Computational Linguistics
Country/TerritorySweden
CityGothenburg
Period2017/05/232017/05/24

Subject classification (UKÄ)

  • Language Technology (Computational Linguistics)

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