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.
S. Blodgett, S. Barocas, H. Daumé III, and H. Wallach. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, page 5454--5476. Online, Association for Computational Linguistics, (July 2020)
L. Flek. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, page 7828--7838. Online, Association for Computational Linguistics, (July 2020)
M. Peters, M. Neumann, R. Logan, R. Schwartz, V. Joshi, S. Singh, and N. Smith. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), page 43--54. Hong Kong, China, Association for Computational Linguistics, (November 2019)
S. Bordia, and S. Bowman. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, page 7--15. Minneapolis, Minnesota, Association for Computational Linguistics, (June 2019)