Model

Mistral NeMO

Test

Data extraction

Scenario

All valid emails

Run ID

2024-07-18-01J33SZ037104C29H01DGRJKA7

Model input

User/Human
Extract all valid email addresses from the text. Return them in a comma-separated list without spaces. Contact information: 1. John Doe - john.doe@example.com 2. Jane Smith - jane@smith-family.net 3. support@company.co.uk 4. info@subdomain.example.org 5. Invalid email: not.an.email.com 6. Another invalid: @missing-username.com

Model response

AI
Here is a Python solution using regular expressions: ```python import re text = """ Contact information: 1. John Doe - john.doe@example.com 2. Jane Smith - jane@smith-family.net 3. support@company.co.uk 4. info@subdomain.example.org 5. Invalid email: not.an.email.com 6. Another invalid: @missing-username.com """ # Regular expression pattern for email addresses pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b' # Find all matches in the text emails = re.findall(pattern, text) # Join the emails into a comma-separated list emails_list = ','.join(emails) print(emails_list) ``` This will output: ``` john.doe@example.com,jane@smith-family.net,support@company.co.uk,info@subdomain.example.org ```

Evaluation details

Result Evaluator Details Meta Data
Pass Contains a list of texts
john.doe@example.com jane@smith-family.net support@company.co.uk info@subdomain.example.org
john.doe@example.comtrue
jane@smith-family.nettrue
support@company.co.uktrue
info@subdomain.example.orgtrue