Stanford CoreNLP provides a set of natural language analysis tools. It can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract open-class relations between mentions, etc.
The Natural Programming Project is working on making programming languages and environments easier to learn, more effective, and less error prone. We are taking a human-centered approach, first studying how people perform their tasks and then designing languages and environments around people's natural tendencies. We focus on all kinds of programming, including professional programmers, novice programmers who are trying to learn to be experts, and end users, who program to support other jobs or hobbies, such as multimedia authoring, simulations, teaching, prototyping, and other activities supported by computing.
J. Choi, A. Khlif, and E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), page 23--27. Online, Association for Computational Linguistics, (2020)
J. Choi, A. Khlif, and E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), page 23--27. Online, Association for Computational Linguistics, (2020)
M. Schwab, R. Jäschke, and F. Fischer. Proceedings of the 6th International Conference on Natural Language and Speech Processing, page 99--109. Association for Computational Linguistics, (2023)
F. Haak. Information between Data and Knowledge, volume 74 of Schriften zur Informationswissenschaft, Werner Hülsbusch, Glückstadt, Gerhard Lustig Award Papers.(2021)