Tutorials
We provide step-by-step guides to get you started. We cover the following use-cases:
Spacy representations
Learn the basics of how documents are represented with spaCy.
Matching a terminology
Extract phrases that belong to a given terminology.
Qualifying entities
Ensure extracted concepts are not invalidated by linguistic modulation.
Detecting dates
Detect and parse dates in a text.
Processing multiple texts
Improve the inference speed of your pipeline
Detecting hospitalisation reason
Identify spans mentioning the reason for hospitalisation or tag entities as the reason.
↵ Detecting false endlines
Classify each line end and add the excluded
attribute to these tokens.
Aggregating results
Aggregate the results of your pipeline at the document level.
FastAPI
Deploy your pipeline as an API.
Make a training script
Learn how to train a NER pipeline with EDS-NLP.