When doing any sort of natural language processing, the meaning of text can change dramatically if a concept is negated or not. For example, if your application is taking actions based on customer text messages, it is important to know the difference between “I want to cancel my reservation” and “I don’t want to cancel my reservation”. NegEx is a popular algorithm developed by Dr. Wendy Chapman. Since spaCy lacked native negation support, Jeno Pizarro decided to implement the NegEx algorithm as a spaCy pipeline component so it could be easily added to NLP workflows.
This is a personal project but it fits within the larger spaCy Natural Language Processing (NLP) universe.
SpaCy is a great framework for developing NLP applications because it is quite fast and supports processing pipelines. This makes it easy to pick up and utilize components from other developers for your own purposes.