Named-entity recognition (NER) aims at identifying entities of interest in a text.
In this paper we show that reporting a single performance score is insufficient to compare non-deterministic approaches.
Today when many practitioners run basic NLP on the entire web and large-volume traffic, faster methods are paramount to saving time and energy costs.
#4 best model for Named Entity Recognition (NER) on Ontonotes v5 (English)
Determining semantic textual similarity is a core research subject in natural language processing.
Machine translation is a natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings on candidate translations to guide a system to improve.