Hands-On Natural Language Processing with Python

Model

As discussed earlier, we can consider the problem of named entity recognition a sequence problem. A common deep learning approach, followed by most NLP systems, is to use RNNs. However, before we decide on the architecture for our RNN model, we need to think about how we will be providing our input and processing the output from our model.

As our input data is in the form of words, we need a dense vector representation for each word, . Such a representation is also known as a word embedding; commonly available, pretrained word embeddings include Word2vec, GloVe, and fastText. Such pretrained word vectors provide very good semantic representations ...