According to the huggingface blog, neuralcoref is an adaptation of Improving Coreference Resolution by Learning Entity-Level Distributed Representations, which has an accuracy of 65.29 on Ontonotes.
There is a market for making SOTA papers more available and easily useable. It's a real need. Spacy here is an excellent choice. However.. 65.29 is mediocre.
The state of the art in 2021 is 81% of accuracy AKA a 16 % increase.. This makes the difference between a cool demo and something that can begin to become used in the industry.
As a reminder, the SOTA of every NLP/NLU task is easily available and generally up to date on https://paperswithcode.com/sota/coreference-resolution-on-ontonotes
According to the huggingface blog, neuralcoref is an adaptation of Improving Coreference Resolution by Learning Entity-Level Distributed Representations, which has an accuracy of 65.29 on Ontonotes. There is a market for making SOTA papers more available and easily useable. It's a real need. Spacy here is an excellent choice. However.. 65.29 is mediocre. The state of the art in 2021 is 81% of accuracy AKA a 16 % increase.. This makes the difference between a cool demo and something that can begin to become used in the industry. As a reminder, the SOTA of every NLP/NLU task is easily available and generally up to date on https://paperswithcode.com/sota/coreference-resolution-on-ontonotes