Visible to the public Don'T Compare Apples to Oranges: Extending GERBIL for a Fine Grained NEL Evaluation

TitleDon'T Compare Apples to Oranges: Extending GERBIL for a Fine Grained NEL Evaluation
Publication TypeConference Paper
Year of Publication2016
AuthorsWaitelonis, Jörg, Jürges, Henrik, Sack, Harald
Conference NameProceedings of the 12th International Conference on Semantic Systems
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4752-5
Keywordsadaptive filtering, pubcrawl, Resiliency, scalabilty
AbstractIn recent years, named entity linking (NEL) tools were primarily developed as general approaches, whereas today numerous tools are focusing on specific domains such as e.g. the mapping of persons and organizations only, or the annotation of locations or events in microposts. However, the available benchmark datasets used for the evaluation of NEL tools do not reflect this focalizing trend. We have analyzed the evaluation process applied in the NEL benchmarking framework GERBIL [16] and its benchmark datasets. Based on these insights we extend the GERBIL framework to enable a more fine grained evaluation and in deep analysis of the used benchmark datasets according to different emphases. In this paper, we present the implementation of an adaptive filter for arbitrary entities as well as a system to automatically measure benchmark dataset properties, such as the extent of content-related ambiguity and diversity. The implementation as well as a result visualization are integrated in the publicly available GERBIL framework.
URLhttp://doi.acm.org/10.1145/2993318.2993334
DOI10.1145/2993318.2993334
Citation Keywaitelonis_dont_2016