New GERBIL release v1.2.5 – Benchmarking entity annotation systems

Dear all,
the Smart Data Management competence center at AKSW is happy to announce GERBIL 1.2.5.

GERBIL is a general entity annotation benchmarking system and offers an easy-to-use web-based platform for the agile comparison of annotators using multiple datasets and uniform measuring approaches. To add a tool to GERBIL, all the end user has to do is to provide a URL to a REST interface to its tool which abides by a given specification. The integration and benchmarking of the tool against user-specified datasets is then carried out automatically by the GERBIL platform. Currently, our platform provides results for **20 annotators** and **46 datasets** with more coming.

GitHub page:

New features include:

  • Added annotators (DoSeR, NERFGUN, PBOH, xLisa)
  • Added datasets (Derczynski, ERD14 and GERDAQ, Microposts 2015 and 2016, Ritter, Senseval 2 and 3, UMBC, WSDM 2012)
  • Introduced the RT2KB experiment type that comprises recognition and typing of entities
  • Introduced index based sameAs relation retrieval and entity checking for KBs that do not change very often (e.g., DBpedia). Downloading the indexes is optional and GERBIL can run without them (but has the same performance drawbacks as the last versions).
  • A warning should be shown in the GUI if the server is busy at the moment.
  • Implemented checks for certain datasets and annotators. If dataset files are missing (because of licenses) or API keys of annotators, they are not available in the front end.

We want to thank everyone who helped to create this release, in particular we want to thank Felix Conrads and Jonathan Huthmann. We also acknowledge support by the DIESEL, QAMEL and HOBBIT projects.

We really appreciate feedback and are open to collaborations.
If you happen to have use cases utilizing this dataset, please contact us.

Michael and Ricardo on behalf of the GERBIL team

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