GERBIL: General Entity Annotation Benchmark Framework

GERBIL is a general entity annotation system.

Source Code Demo Issues Wiki

Overview of GERBIL
The need to bridge between the unstructured data on the document Web and the structured data on the Data Web has led to the development of a considerable number of annotation tools. Those tools are hard to compare since published results are calculated on diverse datasets and measured in different units.

We present GERBIL, a general entity annotation system based on the BAT-Framework. GERBIL 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 9 annotators and 19 datasets with more coming. Internally, GERBIL is based on the Natural Language Programming Interchange Format (NIF) and provide Java classes for implementing APIs for datasets and annotators to NIF.

If you want to know more, please have a look at our novel paper about GERBIL currently undersubmission at SWJ http://www.semantic-web-journal.net/content/gerbil-%E2%80%93-benchmarking-named-entityrecognition-and-linking-consistently

We also used GERBIL to develop a novel benchmarking system for question answering (QA). Have a look http://www.semantic-web-journal.net/content/benchmarking-question-answering-systems

BAT-Framework GERBIL 1.0.0 GERBIL1.2.5 Experiment
Wikipedia Miner (✔) A2KB
Illinois Wikifier (✔) A2KB
Spotlight A2KB
AIDA A2KB
TagMe 2 A2KB
NERD-ML A2KB
KEA A2KB
WAT A2KB
Dexter A2KB
AGDISTIS (✔) D2KB
Babelfy A2KB
FOX OKE Task 1
FRED OKE Task 1
FREME OKE Task 1
entityclassifier.eu A2KB
CETUS OKE Task 2
xLisa A2KB
DoSer D2KB
PBOH D2KB
NERFGUN D2KB
NIF-based Annotator any

The following table lists the annotators that are currently available and the experiment types they support. Note that some of the A2KB annotators support the D2KB experiment by offering an own API method. Other A2KB annotators can be chosen for a D2KB experiment as well as described in the wiki. However, since the comparison might not be fair, we marked these annotators with (✔) in the table. The same is done for Entity Typing.

A2KB, C2KB,
Entity Recognition
D2KB Entity
Typing
OKE Task 1 OKE Task 2
AIDA (✔)
AGDISTIS
Babelfy
CETUS
CETUS (FOX)
Dexter (✔)
entityclassifier.eu (✔)
FRED (✔) (✔)
FREME e-Entity
FOX (✔) (✔)
KEA
NERD-ML (✔)
Spotlight
TagMe 2 (✔)
WAT
xLisa (✔)
PBoH
NERFGUN
DoSER

The following table lists the datasets that are currently available and the experiment types they support.

A2KB, C2KB, D2KB,
Entity Recognition
Entity Typing OKE Task 1 OKE Task 2
AIDA/CoNLL-Complete
AIDA/CoNLL-Test A
AIDA/CoNLL-Test B
AIDA/CoNLL-Training
AQUAINT
DBpediaSpotlight
Dercyznski
IITB
KORE50
MSNBC
Microposts 2013-Test
Microposts 2013-Train
Microposts 2014-Test
Microposts 2014-Train
Microposts 2015-Test
Microposts 2015-Train
Microposts 2015-Dev
Microposts 2016-Test
Microposts 2016-Train
Microposts 2016-Dev
N3-RSS-500
N3-Reuters-128
OKE 2015 Task 1 evaluation dataset
OKE 2015 Task 1 example set
OKE 2015 Task 1 gold standard sample
OKE 2015 Task 2 evaluation dataset
OKE 2015 Task 2 example set
OKE 2015 Task 2 gold standard sample
Senseval 2
Senseval 3
UMBC
WSDM 2012

Long term stability

The idea of GERBIL emerged in September 2014 when a couple of articles released at the same time claimed to be state-of-the-art. Especially, those approaches were not easily comparable due to their heterogeneous set-up, dataset use and evaluation metrics. Thus, we decided to build GERBIL and extend the BAT-Framework to break the barriers for people not able to write source code. GERBIL is still a young project and thus we are trying to explore the borders of our endeavour. As GERBIL has been launched within two PhD projects funded by European Social Fund we are confident that it will be a long lasting web service. The fallback is our working group AKSW which currently already hosts more than 30 open source projects. Finally, GERBIL is open source software which can be maintained and hosted by anybody.

Furthermore, the research and development unit of the University Leipzig Computation Center keeps daily backups to ensure long-term quotability.

With this project we aim at establishing a highly available, easy quotable and liable focal point for NER and NED evaluations. Additionally, we build our framework to be rapidly extensible and adaptable for future uses.

The survey data from our paper can be found at GERBIL's GitHub repository.

Contributors

  • Ciro Baron (University Leipzig, Germany)
  • Andreas Both (R&D, Unister GmbH, Germany)
  • Martin Brümmer (University Leipzig, Germany)
  • Diego Ceccarelli (Unversity Pisa, Italy)
  • Marco Cornolti (University of Pisa, Italy)
  • Didier Cherix (R&D, Unister GmbH, Germany)
  • Bernd Eickmann (R&D, Unister GmbH, Germany)
  • Paolo Ferragina (University of Pisa, Italy)
  • Christiane Lemke (R&D, Unister GmbH, Germany)
  • Andrea Moro (Sapienza University of Rome, Italy)
  • Roberto Navigli (Sapienza University of Rome, Italy)
  • Francesco Piccinno (University of Pisa, Italy)
  • Giuseppe Rizzo (EURECOM, France)
  • Harald Sack (HPI Potsdam, Germany)
  • René Speck (Institute for Applied Informatics, Germany)
  • Raphaël Troncy (EURECOM, France)
  • Jörg Waitelonis (HPI Potsdam, Germany)
  • Lars Wesemann (R&D, Unister GmbH, Germany)

Publications

by (Editors: ) [BibTex of ]

News

AKSW Colloquium, 07.07.2017, Two paper presentations concerning Link Discovery and Knowledge Base Reasoning ( 2017-07-06T21:24:36+02:00 by Daniel Obraczka)

2017-07-06T21:24:36+02:00 by Daniel Obraczka

At the AKSW Colloquium on Friday 7th of July, at 10:40 AM there will be two paper presentations concerning genetic algorithms to learn linkage rules, and differentiable learning of logical rules for knowledge base reasoning. Read more about "AKSW Colloquium, 07.07.2017, Two paper presentations concerning Link Discovery and Knowledge Base Reasoning"

SANSA 0.2 (Semantic Analytics Stack) Released ( 2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann)

2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann

The AKSW and Smart Data Analytics groups are happy to announce SANSA 0.2 – the second release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.2 (Semantic Analytics Stack) Released"

AKSW at ESWC 2017 ( 2017-06-12T10:53:35+02:00 Christopher Schulz)

2017-06-12T10:53:35+02:00 Christopher Schulz

Hello Community! The ESWC 2017 just ended and we give a short report of the course at the conference, especially regarding the AKSW-Group. Our members Dr. Muhammad Saleem, Dr. Mohamed Ahmed Sherif, Claus Stadler, Michael Röder, Prof. Dr. Read more about "AKSW at ESWC 2017"

Four papers accepted at WI 2017 ( 2017-06-10T15:01:31+02:00 Christopher Schulz)

2017-06-10T15:01:31+02:00 Christopher Schulz

Hello Community! We proudly announce that The International Conference on Web Intelligence (WI) accepted four papers by our group. The WI takes place in Leipzig between the 23th – 26th of August. Read more about "Four papers accepted at WI 2017"

AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data. ( 2017-05-26T13:51:11+02:00 by Diego Moussallem)

2017-05-26T13:51:11+02:00 by Diego Moussallem

At the AKSW Colloquium, on Monday 29th of May 2017, 3 PM, Diego Moussallem will present two papers related to his topic. First paper titled “Using BabelNet to Improve OOV Coverage in SMT” of Du et al. Read more about "AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data."