Removing Language Barrier with AI – A Practical Example

On, we provide different types of information about a mosque including a general description or overview. Originally, this overview section was meant to be meticulously crafted by our editorial team. However, since English is not the first language for many of our data mining team members, they often felt uncertain about writing the descriptions themselves. When they did write them, the results were frequently unsatisfactory due to poor composition and grammatical mistakes.

This issue remained unresolved for quite a long time, largely due to our non-profit budget constraints. But recently, a spark of innovation led us to a solution: leveraging AI to overcome this challenge.

In our backend API, we designed a prompt containing the information we believed would be valuable. We then made an API call to the gpt-3.5-turbo model, which in turn generated a description based on the provided details. Here’s an example:

Generate a human-friendly brief description for the mosque based on the provided data within Beginning & end of Data Section. Adhere to the following guidelines:

<A number of rules; redacted for brevity>

Beginning of Data Section
<Provided data about mosques; redacted for brevity>
End of Data Section


We have noticed that the generated content occasionally deviates from our instructions. However, with the availability of gpt-4, we anticipate a significant improvement that will bring us closer to our goal of providing accurate and engaging descriptions for our users.

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