vhandit

Check out my implementation here Background I wanted to have a tool for human beings to classify intents and extract entities of texts which were obtained from a raw dataset such as Rocket.chat's conversation, Maluuba Frames or  here . Then, the output (labeled texts) could be consumed by an NLU tool such as Rasa NLU. rasa-nlu-trainer was a potential one which I didn't need to build an app from scratch. However, I needed to add more of my own features to fulfill my needs. They were: 1. Loading/displaying raw texts stored by a database such as MongoDB 2. Manually labeling intents and entities for the loaded texts 3. Persisting labeled texts into the database I firstly did look up what rasa-nlu-trainer 's technologies were used in order to see how to implement my mentioned features. At first glance rasa-nlu-trainer was bootstrapped with Create React App. Create React App is a tool to create a React app with no build configuration, as it said. This too