NanoNER: Named Entity Recognition for nanobiology using experts' knowledge and distant supervision

Here we present the training and evaluation of NanoNER, a Named Entity Recognition (NER) model for Nanobiology. NER consists in the identification of specific entities in spans of unstructured texts and is often a primary task in Natural Language Processing (NLP) and Information Extraction. The aim of our model is to recognise entities previously identified by domain experts as constituting the essential knowledge of the domain. Relying on ontologies, which provide us with a domain vocabulary and taxonomy, we implemented …

aim cs.ai cs.cl cs.ir evaluation experts extraction identification information information extraction knowledge language language processing natural natural language natural language processing ner nlp processing recognition supervision training unstructured