While the model trained by HS is efficient to evaluate perplexities, NCE training requires summation over all words in the vocabulary in the denominator of the softmax to compute perplexity, an impracticality for large vocabulary.
as discussed in Section 3.3, the pipeline method, although commonly used in deep learning literatures, does not suit NLP applications well because of the sparsity in word embeddings.