This article describes the development of a tense and aspect identifier, an online tool designed to help learners of English by harnessing a natural language processing pipeline to automatically classify verb groups into one of 12 grammatical tenses. Currently, there is no website or application that can automatically identify tense in context, and the tense and aspect identifier fills that niche. Learners can use the tool to see how grammatical tenses are used in context. Finite verb groups are automatically identified, and the relevant words in the verb group are highlighted and colorized according to the tense identified. The latest deployed system can identify tenses in simple, compound, and complex sentences. False positive results occur when there is ellipsis of auxiliary verbs or when the tagger assigns the incorrect part-of-speech tag. The user interface of the tense identifier is a web app created using the Flask framework and deployed from the Heroku platform. The tool can be used for inductive and deductive teaching approaches, or even to check for tense consistency in a thesis. [For the complete volume, "CALL for Widening Participation: Short Papers from EUROCALL 2020 (28th, Online, August 20-21, 2020)," see ED610330.]