Papers › The Biomaterials Annotator: a system for ontology-based concept annotation of biomaterials text

The Biomaterials Annotator: a system for ontology-based concept annotation of biomaterials text

1 Jun 2021NAACL (sdp) 2021 6archive 2025-07-28

Javier Corvi, Carla Fuenteslópez, José Fernández, Josep Gelpi, Maria-Pau Ginebra, Salvador Capella-Guitierrez, Osnat Hakimi

Biomaterials are synthetic or natural materials used for constructing artificial organs, fabricating prostheses, or replacing tissues. The last century saw the development of thousands of novel biomaterials and, as a result, an exponential increase in scientific publications in the field. Large-scale analysis of biomaterials and their performance could enable data-driven material selection and implant design. However, such analysis requires identification and organization of concepts, such as materials and structures, from published texts. To facilitate future information extraction and the application of machine-learning techniques, we developed a semantic annotator specifically tailored for the biomaterials literature. The Biomaterials Annotator has been implemented following a modular organization using software containers for the different components and orchestrated using Nextflow as workflow manager. Natural language processing (NLP) components are mainly developed in Java. This set-up has allowed named entity recognition of seventeen classes relevant to the biomaterials domain. Here we detail the development, evaluation and performance of the system, as well as the release of the first collection of annotated biomaterials abstracts. We make both the corpus and system available to the community to promote future efforts in the field and contribute towards its sustainability.

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Named Entity RecognitionNamed Entity Recognition (NER)named-entity-recognition

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