An empirical evaluation of ontology-based semantic annotators

Srecko Joksimovic, Jelena Jovanovic, Dragan Gasevic, Amal Zouaq, Zoran Jeremic

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

7 Citations (Scopus)


One of the most important prerequisites for achieving the Semantic Web vision is semantic annotation of data/resources. Semantic annotation enriches unstructured and/or semi-structured content with a context that is further linked to the structured domain-specific knowledge. In particular, ontology-based semantic annotators enable the selection of a specific ontology to annotate content. This paper presents results of an empirical study of recent ontology-based annotators, namely Stanbol, KIM, and SDArch. Specifically, we evaluated the robustness of these annotators with respect to specific features of ontology concepts such as the length of concepts' labels and their linguistic categories (e.g., prepositions and conjunctions). Our results show that although significantly correlated according to most of the conducted evaluations, tools still exhibit their unique features that could be a topic of new research.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Knowledge Capture
Subtitle of host publication"Knowledge Capture in the Age of Massive Web Data", K-CAP 2013
Publication statusPublished - 2 Sep 2013
Externally publishedYes
EventKnowledge Capture 2013 - Banff, Canada
Duration: 23 Jun 201326 Jun 2013
Conference number: 7th


ConferenceKnowledge Capture 2013
Abbreviated titleK-CAP 2013
Internet address


  • Annotation tools
  • Automatic semantic annotation
  • Comparative analysis
  • Empirical study

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