Introduction

A noun detector is a tool or algorithm designed to identify and extract nouns from a given text or speech input. Nouns are a type of word that typically represent people, places, things, or ideas. In the context of chat-based applications, a noun detector can be useful for extracting key information or identifying specific entities mentioned in a conversation. It can help in tasks such as named entity recognition, information retrieval, sentiment analysis, and many more.
A noun detector serves as a valuable component in language processing systems, helping to extract and utilize meaningful information from text or speech inputs in chat-based interactions.

Logic

First, ChatGPT generates random sentences, and we save this response in a variable. Then, it asks users to identify a noun from the given sentence. If the user’s answer matches the response generated by ChatGPT, it will say “Correct.” Otherwise, it will say “Incorrect answer.”

1. Open PictoBlox and create a new file.
2. Select the environment as appropriate Block Coding Environment.
3. To add the ChatGPT extension, click on the extension button located as shown in the image. This will enable the ChatGPT extension, allowing you to incorporate its capabilities into your project.
   
4. We drag and drop the “Ask (AI)” block from the ChatExtension, and we use it to ask for any random sentence as input from chatGPT.
   
5. We create a new variable called sentence and assign the value of a random sentence generated by ChatGPT to it.
   
6. Use the say() method to provide instructions for finding nouns in the given sentence.
7. Drag and drop the get() from the () block from the ChatGPT extension to obtain information from the sentence.
   
8. If we use an if-else loop, we prompt the user to identify a noun from a given sentence. If the user’s answer matches the response generated by ChatGPT, it will say Correct answer for 2 minutes.
9. Otherwise, if the user’s answer does not match the response from ChatGPT, it will return Answer is not a noun for 2 seconds.
10. To begin the script, simply click on the green flag button.

Code

Output