Remixing Entity Linking Evaluation Datasets for Focused Benchmarking

Tracking #: 1583-2795

This paper is currently under review
Jörg Waitelonis
Henrik Jürges
Harald Sack

Responsible editor: 
Guest Editors Benchmarking Linked Data 2017

Submission type: 
Full Paper
In recent years, named entity linking (NEL) tools were primarily developed in terms of a general approach, 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 necessary 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 [17] and all its benchmark datasets. Based on these insights we have extended the GERBIL framework to enable a more fine grained evaluation and in depth analysis of the available benchmark datasets with respect to different emphases.This paper presents the implementation of an adaptive filter for arbitrary entities and customized benchmark creation as well as the automated determination of typical NEL benchmark dataset properties, such as the extent of content-related ambiguity and diversity. These properties are integrated on different levels, which also enables to tailor customized new datasets out of the existing ones by remixing documents based on desired emphases. The implemented system as well as an adapted result visualization has been integrated in the publicly available GERBIL framework. In addition, a new system library to enrich provided NIF [3] datasets with statistical information including best practices for dataset remixing are presented.
Full PDF Version: 
Under Review