Data · dataset · 2022
lavis-nlp/german_legal_sentences
Listed in Hugging Face Datasets
German Legal Sentences (GLS) is an automatically generated training dataset for semantic sentence matching in the domain in german legal documents.
Description
It follows the concept of weak supervision, where imperfect labels are generated using multiple heuristics. For this purpose we use a combination of legal citation matching and BM25 similarity.
The contained sentences and their citations are parsed from real judicial decisions provided by Open Legal Data
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/lavis-nlp/german_legal_sentences ↗
landing page · from Hugging Face
Documentation and papers
- arXiv:2005.13342 arxiv.org/abs/2005.13342 ↗
publication · from Hugging Face
- arXiv:2010.10252 arxiv.org/abs/2010.10252 ↗
publication · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/lavis-nlp/german_legal_sentences ↗
metadata API · from Hugging Face
Topics
- Stated by source
- text retrieval
- From keywords
- Computer Science & AI
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | lavis-nlp/german_legal_sentences | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| concepts[task].hf_task:text-retrieval | source · Hugging Face | connector:huggingface@1.0.0 | /tags[task_categories:*] |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| license_text | source · Hugging Face | connector:huggingface@1.0.0 | |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |