ArticleJournal of biomedical semantics2013
Monitoring named entity recognition: the League Table.
Article in Journal of biomedical semantics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Combining lexical and context features for automatic ontology extension.Journal of biomedical semantics · 2020Article
- Benchmarking infrastructure for mutation text mining.Journal of biomedical semantics · 2014Article
- Evaluating gold standard corpora against gene/protein tagging solutions and lexical resources.Journal of biomedical semantics · 2013Article
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Authors and funding
5 authors.
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Abstract
backgroundNamed entity recognition (NER) is an essential step in automatic text processing pipelines. A number of solutions have been presented and evaluated against gold standard corpora (GSC). The benchmarking against GSCs is crucial, but left to the individual researcher. Herewith we present a League Table web site, which benchmarks NER solutions against selected public GSCs, maintains a ranked list and archives the annotated corpus for future comparisons.
resultsThe web site enables access to the different GSCs in a standardized format (IeXML). Upon submission of the annotated corpus the user has to describe the specification of the used solution and then uploads the annotated corpus for evaluation. The performance of the system is measured against one or more GSCs and the results are then added to the web site ("League Table"). It displays currently the results from publicly available NER solutions from the Whatizit infrastructure for future comparisons.
conclusionThe League Table enables the evaluation of NER solutions in a standardized infrastructure and monitors the results long-term. For access please go to http://wwwdev.ebi.ac.uk/Rebholz-srv/calbc/assessmentGSC/. CONTACT: rebholz@ifi.uzh.ch.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.