Training Custom Models for Text Analysis in Knime

Hi everyone,

I need some guidance regarding text document analysis in Knime. I’ve explored various techniques for analyzing text, particularly utilizing the Spacy library for recognizing names, entities, and more.

This task is something I’m keen to pursue, but with a focus on specific data such as drug names, laboratory names, and disease names. Is it viable to train a custom model using Spacy to identify these specific entities, utilizing a dataset containing text and associated labels?

Moreover, I’m interested in generalizing the model to identify new matches beyond the training dataset. While I’m aware of achieving this through Python code, I’m unsure if the Redfield NLP Node extension offers similar capabilities.

I appreciate any assistance you can provide on this matter.