In this video, we continue exploring named entity recognition (NER) for the digital humanities in Python, specifically via the spaCy library. In this video, we use the EntityRuler model that we created in the last video to generate automatically a strong training set. We will use this NER training set in the next video to train a custom domain-specific NER machine learning model in spaCy. This will allow us to migrate the approach from rules-based to machine learning based. This is the first step to making a state-of-the-art model on Harry Potter.
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