Lazy OCR, text layer, and PDF backend.

### Question
Dear all,
I still do not have clear in my had the functioning of the pdf backend and what happens under the hood for a basic pdf conversion:
If I use the following pipeline:
```
pipeline_options = PdfPipelineOptions()
pipeline_options.do_ocr = False
pipeline_options.do_table_structure = False
pipeline_options.table_structure_options.do_cell_matching = False

doc_converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_options=pipeline_options, backend=PyPdfiumDocumentBackend
)
}
)
```
Even with this simple pipeline the conversion takes some time with a longer document. I am pretty sure there is a text layer already and if not I would like to skip the whole processing of document anyway since I will not have the resources do it (btw is there a way to check with Docling). I am forcingly disabling the process of OCR and table extraction. Why would than take more time than a normal pdf package to spit the text out?
I suppose that since Docling Document object contains much more information about the structure then just the text... is such rendering process that takes some time? What is it exactly happening under the hood (visual model/ rendering)?
I also tested the time for conversion to markdown and is pretty fast and accurate so I suppose that the converted document object contains all this structural information already. My last question is than: Is this rendering process using the existing text layer? What would it do with a pdf that does not have an embedded text layer already and OCR is disabled?

Thanks for your time and patience