German Legal Documents for Named Entity Recognition

Made up of German legal documents annotated for Named Entity Recognition tasks. It was created by author elenanereiss and was last updated in October 2022.

Use Cases

• Train a BiLSTM-CRF model on annotated German legal texts for Named Entity Recognition.
• Fine-tune a German language model on legal entity annotations to extract specific legal terms.
• Analyze the distribution and co-occurrence of named entities within German legal documents.

Strengths

• Dataset is specifically focused on German legal texts, a specialized domain.
• Last update was recorded on October 19, 2022, providing a timestamp for the data.

Limitations

• The dataset size, row count, and specific column structure are unknown.
• The absence of sample data and file format details makes initial assessment difficult.

Provenance

Source

github, author elenanereiss

Freshness

Last updated 2022-10-19.

Geography

Germany (inferred from language and domain)