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-Edit this `README.md` markdown file to author your organization card.
+# OTAR3088 NLP-model organisation
+
+## Work Package 1 - Knowledge Extraction (NLP)
+
+_**Background**_
+
+Within this working group of the greater _OTAR3088, 'Automating Knowledge Management'_ project, we aim to modernise and extend the current named entity recognition workflows of EuropePMC / Open Targets to cover an array of entity types of entities relevant to drug discovery (such as variants, biomarkers, tissues/cell types, adverse events, and assay conditions). These new entities will provide higher confidence in the relevance of a target-disease association.
+
+Since NLP models are constantly updated and fine-tuned, we have created a modular, flexible framework that facilitates the creation of new NLP models.
+
+_**OTAR3088 HuggingFace**_
+
+This organisation space details all of the data development and model generation of the project. Data is sectioned by the greater entity-type being studied by the group at a given time, sources of data are described in the data cards. Output models are also shared here.
+
+
+_**Learn more about our project, resources and others:**_
+
+* [OTAR3088 - The project](https://aws.amazon.com/ec2/instance-types/g4/?trk=5767130d-03c1-443e-908e-5202162d30d3&sc_channel=el)
+* [Our flexible NLP-model production pipeline](https://github.com/ML4LitS/OTAR3088)
+* [Helpful wider-context reading](https://www.tandfonline.com/doi/full/10.1080/17460441.2025.2490835)