The foundation of successful named entity recognition (NER) within biomedical text comes from high quality reference vocabularies or thesauri.
Until now, crafting a high quality vocabulary from scratch or customising an existing one with in-house domain knowledge has been a complicated and tedious process. Scientists either juggle multiple text files, or use complex ontology editors that turn simple editing tasks into lengthy procedures.
In our research, we found that many customers are resorting to tools like Microsoft Excel, which, although simple to use, aren’t built for the management of complex scientific data.
Our Vocabulary Editing Toolkit (VET) is SciBite’s answer to the challenge. Designed for those wanting to adapt existing or curate entirely new vocabularies, VET is an editor that “understands” vocabularies – synonyms, unique identifiers and taxonomy, providing crucial functionality such as real-time sanity checks on your vocabulary’s integrity for quality assurance.
Human curators will enjoy a smoother editing experience and achieve higher throughput, thanks to VET’s clutter-free display and ergonomic features, minimising keystrokes and eliminating constant switching between keyboard and mouse.
Get in touch with us to find out how we can transform your data.
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