Prompt Details
Model
Chat - (gpt-5.6)
Token size
320
Example input
[RAW TEXT]: Ana Souza <ana.souza@gmail.com> tel (11) 98877-1234bruno lima - brunolima@outlook.com - 11 977665544Carla: carla.medeiros@empresa.com.br, fone 11-91234-9876diego fernandes DIEGO.F@GMAIL.COM (11)97654 3210
[FORMAT: CSV or JSON]: CSV
[SCHEMA]: name, email, phone
[STRICTNESS: lenient or strict]: strict
Example output
Schema confirmed: name, email, phone.
name,email,phone
Ana Souza,ana.souza@gmail.com,11988771234
bruno lima,brunolima@outlook.com,11977665544
Carla,carla.medeiros@empresa.com.br,11912349876
diego fernandes,diego.f@gmail.com,11976543210
Unsure rows:
- Carla: only a first name was given. Kept as is; you may want the surname before using this.
- diego fernandes: email arrived in all caps (DIEGO.F@GMAIL.COM). Lowercased, which is standard for the domain part; the local part is technically case-sensitive but Gmail treats it as case-insensitive, so this is safe.
- All phones: normalized to digits only, no country code. If you need +55, say so and I will add it.
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GPT-5.6
Paste messy text (email dumps, copied tables, notes, logs) and get back clean CSV or JSON with a real schema, consistent dates, and an honesty list of every cell it could not parse. No silent guesses, no invented values. Built for people who clean data by hand too often.
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Added over 1 month ago
