Updated on December 21, 2023
In the fields of robot systems and natural language processing, intelligent chatbots and dialogue systems are a hot topic. As natural language processing and neural network algorithms advance, so does the use of artificial intelligence in Chatbot systems, which are typically used in dialogue systems for a variety of practical purposes such as customer service or information acquisition.
To create a responsive chatbot, we can automatically extract information from the conversation and create a structured chat using Entities. An entity is used in a chatbot to add values to the search intent. An entity, also known as a slot, modifies user intent within a chatbot. We can use chatbot entities linked to knowledge repositories to provide more personalised and accurate responses to user searches.
It is critical for an ideal NLP system to parse the user dialogue, detect multiple intents within the dialogue, and capture the entities of that specific intent. The chatbot’s ability to detect the context of the user’s utterance is crucial. Kompose by Kommunicate is one such tool. The following guide will show you how to use Kompose to extract names and use them in conversations. This will allow your chatbot to recognise the users’ names and respond to them by name.
Kompose is a GUI bot builder based on natural language conversations for human-computer interaction. You don’t need to have any coding skills to master Kompose.It has an easy-to-use interface and allows you to extract entities by simply checking a box.
Bonus: Read about Intent Vs Entities
How to Extract and Use Usernames in Kompose Chatbots?
Log in to your Kommunicate dashboard, If you do not yet have a kommunicate account, you can sign up here. Navigate to the Kompose bot builder section from the ‘Bot Integration’ segment and select the bot for which you want to extract the name in the conversation. If you haven’t created your bot yet, you can start by reading our article on “How to Create a Chatbot.“
Create your first welcome message, click on the Default Welcome Intent. This message will prompt the bot to greet the user with the first greeting response. By hitting the ‘Show Preview’ button, you may preview the saved changes instantly.
The “User says” area of the Answer segment can be used to give training phrases, while the “Bot says” section can be used to build a conversation flow. Parts of the phases will be recognised by Kompose, and it will reply to the user accordingly.
Bonus: Read all about NLP chatbot
The “User says” area of the Answer segment can be used to give training phrases, while the “Bot says” section can be used to build a conversation flow. Parts of the phases will be recognised by Kompose, and it will reply to the user accordingly.
Navigate to the bot says segment and add responses to what the user says, Then select the conditions with the Extract entities fields and the desired parameter values.
Save the changes by clicking the “Train Bot” button, and the chatbot can now recognise and remember users’ names and greet them by name. The saved changes can be tested on the Kommunicate chat widget, where they will appear as follows:
In this manner, you can easily extract and use names in the Kompose bot. Similarly, you can extract other parameter values such as email, Url, phone number, and even forward to a webhook if necessary. This will personalise chatbot interactions for a better customer experience.
At Kommunicate, we are envisioning a world-beating customer support solution to empower the new era of customer support. We would love to have you onboard to have a first-hand experience of Kommunicate. You can signup here and start delighting your customers right away.
