Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Dataset Card for "domsdatabasen"

Dataset Summary

Domsdatabasen is a database where you can find and read selected judgments delivered by the Danish Courts.

Each judgment/case consists of tabular data and a case-descriptive PDF. This dataset collects all these cases, with each sample describing a specific judgment/case.

The PDFs are anonymized to protect sensitive information. Therefore, each sample includes two text versions:

text_anon (with anonymization tags: <anonym>"Some sensitive text"</anonym>).
text (without anonymization tags).

text_anon is read with Easyocr.

text is read with Easyocr or Tika-python depending on the PDF and the anonymization method used.

text_anon will be empty if no anonymization is detected in the PDF.

Languages

The dataset is available in Danish (da).

Dataset Structure

An example from the dataset looks as follows.

{
  "case_id": "id of case/judgment",
  ... The tabualar string data ...,
  "text": "pdf text",
  "text_anon": "anonymized pdf text"
  "text_len": <number of chars in text>,
  "text_anon_len": <number of chars in anonymized text>
}