NELL was programmed by its developers to be able to identify a basic set of fundamental semantic relationships between a few hundred predefined categories of data, such as cities, companies, emotions and sports teams. Since the beginning of 2010, the Carnegie Mellon research team has been running NELL around the clock, sifting through hundreds of millions of web pages looking for connections between the information it already knows and what it finds through its search process – to make new connections in a manner that is intended to mimic the way humans learn new information. For example, in encountering the word pair "Pikes Peak", NELL would notice that both words are capitalized and deduce from the second word that it was the name of a mountain, and then build on the relationship of words surrounding those two words to deduce other connections.
Oren Etzioni of the
University of Washington lauded the system's "continuous learning, as if NELL is exercising curiosity on its own, with little human help". Clear errors like these are corrected every few weeks by the members of the research team and the system is allowed to continue its learning process. As of September 2023, the project's most recently gathered facts dated from February 2019 (according to its Twitter feed) or September 2018 (according to its home page). == Reception ==