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Understanding Contexts


In a chatbot conversation, like in real life, the ideal answer to a particular question can depend on the situation. Take the “How big is the team?” question as an example - the answer is probably different if it was asked related to a designer position, compared to a sales position. In order to give you the flexibility to train your chatbot to properly answer such questions, we created contexts. 

Turning a category into a context dependent category will make the chatbot give different answers to the same question depending on the context of the conversation. A typical context is a job position or a group of job positions. The context is set when the candidate selects the job position (typically in the job carousel) and asks a position related question.



Setting up a context dependent category

You can make a category context dependent by checking the checkbox upon category creation on the FAQ page on the dashboard. More information on the process here.

Also, an existing category can be be made context dependent by checking the checkbox in the “category core data” section on the “category” tab of the FAQ page on the dashboard. More information on the process here.

How to handle context specific questions?

Incoming questions are displayed in the list view of the training tab on the FAQ page. If a question has a context set, it’s displayed in the context column:


Click on the such a question will bring up the question approval modal with an option to setup a context dependent answer:


Whenever a context is set and the question belongs to a context dependent category, the context specific answer will be given. If no such response exists yet, the chatbot won't use the category's general answer - you'll have to respond the question, by supplying the answer when training, or via direct answer. In case of context independent categories, the chatbot will always respond with the general answer in every context.