---
language:
- pl
---
# Dataset Card for PES-2018-2022

## Dataset Description

This is a dataset used and described in:
```
@misc{pokrywka2024gpt4,
      title={GPT-4 passes most of the 297 written Polish Board Certification Examinations}, 
      author={Jakub Pokrywka and Jeremi Kaczmarek and Edward Gorzelańczyk},
      year={2024},
      eprint={2405.01589},
      archivePrefix={arXiv},
      primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}
}
```

This dataset is 297 Polish Board Certification Examinations from years 2018-2022.

The Państwowy Egzamin Specjalizacyjny (PES), which translates to English as Polish
Board Certification Exam in English, serves as a crucial assessment for medical
practitioners in Poland, marking the culmination of their specialization process. It is
composed of two parts: a written test with multiple-choice questions and an oral
examination. Its primary objective is to evaluate the proficiency and expertise acquired
during specialized training. The successful completion of the PES, in conjunction with
the requisite courses and qualifying training periods, is obligatory for medical doctors in
Poland to gain official recognition as specialists in their respective fields, thereby
granting them the autonomy to practice their specialty independently.
 

The dataset was published in https://nil.org.pl/aktualnosci/8012-sukces-samorzadu-lekarskiego-nil-udostepniapytania-z-pes and https://nil.org.pl/aktualnosci/8043-kolejne-pytania-z-pesudostepnione%C2%A0 in PDFs as separate exams and exam keys.
I processed them into a convenient JSON format. It's important to note that not all examples from the links were used. Some of them were PDFs with only image and no text layer and these were not used due to their format limitations.

I do not own rights to this dataset; I just processed it and published it here.