Building Lightweight Ontologies for Faceted Search with Named Entity Recognition: Case WarMemoirSampo

Mikko Koho*, Rafael Leal, Esko Ikkala, Minna Tamper, Heikki Rantala, Eero Hyvönen

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

1 Citation (Scopus)
64 Downloads (Pure)

Abstract

This paper discusses building lightweight ontologies for faceted search user interfaces with Named Entity Recognition (NER) from textual data. This is studied in the context of building a Knowledge Graph for the textual indexing of interview videos in the in-use WarMemoirSampo system, consisting of a Linked Open Data service and an open semantic web portal for contextualized video viewing. It is shown that state-of-the-art NER tools are able to find entities from textual data and categorize them with high enough recall and precision to be useful for building facet ontologies, without involving considerable manual domain ontology engineering. To enable entity disambiguation and to be able to show relevant contextual information and useful links for the users of the portal, also Named Entity Linking techniques are employed.

Original languageEnglish
Pages (from-to)19-35
Number of pages17
JournalCEUR Workshop Proceedings
Volume3184
Publication statusPublished - 11 Aug 2022
MoE publication typeA4 Conference publication
EventInternational Workshop on Knowledge Graph Generation from Text - Hersonissos, Greece
Duration: 30 May 202230 May 2022
Conference number: 1

Keywords

  • Faceted Search
  • Information Extraction
  • Linked Data
  • Named Entity Linking
  • Named Entity Recognition
  • Ontologies

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