ChatGPT prompt for: Parse Full Name into First Name, Last Name and Gender

Given a full name and a geographic location (to avoiding gender ambiguity), return the First Name, Last Name and Gender.

Given the full name '%full_name%' and the geographic location '{location}', please:

1. Extract the first name and last name, assuming the most likely common order for first and last names. Prioritize recognizing common first names and last names where possible.
2. Based on the first name and the provided geographic location, infer the gender as 'male', 'female', or 'unknown'. If no clear inference can be made, return 'unknown'.
3. If there are more than two parts to the name (e.g., a middle name or a prefix like 'Dr.'), consider only the first and last name.

Example 1:
- Full Name: 'Kari Johansen'
- Location: 'Finland'
- First Name: 'Kari'
- Last Name: 'Johansen'
- Gender: 'Male'

Example 2:
- Full Name: 'John Michael Doe'
- First Name: 'John'
- Last Name: 'Doe'
- Gender: 'Male'

How to use this prompt on a CSV file?

Datablist allows you to take an entire CSV file and run prompts directly on every line. Whether you're cleaning data, generating summaries, or transforming text, this method saves hours.

The great news is that the prompt you need is already available in Datablist under the "Templates" section. No need to start from scratch! Simply select the template that fits your task, and it’s ready to run on every line of your CSV. This makes it even easier to transform your data with just a few clicks.

Import your CSV file in Datablist. Then select "Enrich" from the header.

Then select the template: Parse Full Name into First Name, Last Name and Gender

Replace the variables from the prompt with your collection's properties using {{