1. Overview
  2. Data Extraction
  3. GPT-Powered Parser

GPT-Powered Parser

For a more advanced GPT-powered parsing, please check out our second product, Airparser (and refer to the "Advanced GPT-Powered Parsing" section of this article)

The GPT-powered parser allows you to extract structured data from emails, PDFs, and files using a text prompt (similar to ChatGPT).

The advantage is that there is no need to create parsing templates or complex parsing rules. Simply specify the desired fields to extract from the document. Feel free to write your prompt in a conversational tone, as if you were talking to a person, but be specific in your description.

Some use cases for the parser are:

  • Parsing complex PDF files (candidates CVs, reports, ...).
  • Parsing emails and tables (SEO reports, Amazon order emails, ...).
  • Parsing human-written emails and texts without a fixed layout that the template-based parser is unable to process (flight details, ...).
  • Extract contact details from email signatures (the email signature parser is also available using the template-based parser).

The prompt is defined at the mailbox level, meaning it is the same for all the documents in that mailbox.

Supported formats: Emails, PDFs, HTML, TXT, DOCX, XML, MD, and JSON.

Parsing PDF Files Using the GPT-powered Parser

1. Create a new inbox and select the GPT-powered parser.

2. Upload a sample CV PDF file.

3. Open the "Prompt Debug" tab and write a prompt. In our case, we will write: Extract from CV: full_name, phone, email, address, work_experience (array of items: year_range, description).

4. Click the "Save & run" button and wait for the parsed data. Note that this is a preview of the parsed data and it's not saved in the document's result (Parsed/JSON tabs).

5. If the parsed result looks correct, you can finally parse your CV by clicking the "Reprocess" button.

All the incoming PDF files in that mailbox will be automatically processed using the same prompt.

If you update the prompt, previously parsed documents will not be automatically reprocessed. You will need to manually click the 'Reprocess' (or 'Reprocess All') button.



The GPT-powered parser doesn't currently support OCR functionality. Therefore, it is unable to parse text from images and scanned PDF files.

Note that GPT parsing can be quite slow, especially if your document is large and you are trying to export many data points. We have observed cases where parsing of one document takes up to 4 minutes. This is due to the nature of OpenAI's API, and it is currently not possible to make it faster. To mitigate this, you can consider requesting less data in your query or splitting your documents into multiple files (for example, parsing PDF pages separately). This approach might help improve the parsing speed.

Data privacy note: Your data is not used to train or improve AI models. Read more about OpenAI's API data usage policies.

Advanced GPT-Powered Parsing

Parsio offers a powerful yet simple GPT parser. You can enter one multiline parsing prompt.

You may consider checking our second product: Airparser (https://airparser.com), which offers a more advanced GPT-powered parser compared to Parsio.

The key distinction is that Airparser allows you to create a structured parsing schema instead of a single text prompt. It also supports OCR for scanned documents and images. Airparser is particularly effective for unstructured and human-written docs.

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