Named Entity Recognition and the Road to Deep Learning

Not so very long ago, Natural Language Processing looked very different. In sequence labelling tasks such as Named Entity Recognition, Conditional Random Fields were the go-to model. The main challenge for NLP engineers consisted in finding good features that captured their data well. Today, deep learning has replaced CRFs at the forefront of sequence labelling, and the focus has shifted from feature engineering to designing and implementing effective neural network architectures. Still, the old and the new-style NLP are not diametrically opposed: just as it is possible (and useful!) to incorporate neural-network features into a CRF, CRFs have influenced some of the best deep learning models for sequence labelling.