datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
legal-doctrine-evolution-coherence-trajectory-v0.1What this dataset is
You receive
doctrine state at t
transition signals
doctrine state at t+1
split or exception signals
workability or legitimacy signals
reform pressure signals
You decide
Is the doctrine evolution stable
Answer
coherent
or
incoherent
Why this matters
Incoherent trajectories predict
overruling events
doctrinal collapse
rapid rule change
institutional instability
legal-judicial-doctrinal-consistency-drift-v0.1What this dataset is
You receive
prior opinion pattern
current opinion pattern
citation shift
test or factor weighting shift
explanation quality
external reaction signals
You decide
Does the judge remain doctrinally consistent
Answer
coherent
or
incoherent
Why this matters
Doctrinal drift predicts
dissents and fractures
en banc pressure
reversal risk
loss of precedential durability
legal_document_structuringTask details
Document structuring plays a crucial role in various natural language processing (NLP) tasks, such as information retrieval, and document understanding.
It also helps readers to effectively navigate into a structured document with a large amount of textual data.
In the legal domain, document structuring is particularly important for creating inter- and intra-document links.
The dataset provides documents segmented into lines.
Each document was collected in HTML format or PDF… See the full description on the dataset page: https://huggingface.co/datasets/DoctrineAI/legal_document_structuring.