1 code implementation • Findings of the Association for Computational Linguistics 2020 • Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury, Srinivas Bangalore
Current state-of-the-art models for named entity recognition (NER) are neural models with a conditional random field (CRF) as the final layer.
1 code implementation • 30 Sep 2020 • Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury, Srinivas Bangalore
Most state-of-the-art models in natural language processing (NLP) are neural models built on top of large, pre-trained, contextual language models that generate representations of words in context and are fine-tuned for the task at hand.
1 code implementation • 5 Jan 2020 • Brian Lester, Daniel Pressel, Amy Hemmeter, Sagnik Ray Choudhury
The CRF layer is used to facilitate global coherence between labels, and the contextual embeddings provide a better representation of words in context.