---
dataset_info:
- config_name: 1k
  features:
  - name: opinion
    dtype: string
  - name: instruction
    dtype: string
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    sequence: int64
  splits:
  - name: test
    num_bytes: 22094474.9
    num_examples: 1000
  download_size: 10004046
  dataset_size: 22094474.9
- config_name: sc
  features:
  - name: opinion
    dtype: string
  - name: instruction
    dtype: string
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    sequence: int64
  - name: task
    dtype: string
  splits:
  - name: test
    num_bytes: 124966347
    num_examples: 5000
  download_size: 48290290
  dataset_size: 124966347
- config_name: songer
  features:
  - name: opinion
    dtype: string
  - name: instruction
    dtype: string
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answer
    sequence: int64
  - name: task
    dtype: string
  splits:
  - name: test
    num_bytes: 82357950
    num_examples: 5000
  download_size: 34691991
  dataset_size: 82357950
configs:
- config_name: 1k
  data_files:
  - split: test
    path: 1k/test-*
- config_name: sc
  data_files:
  - split: test
    path: sc/test-*
- config_name: songer
  data_files:
  - split: test
    path: songer/test-*
---

CaselawQA is a benchmark comprising legal classification tasks, drawing from the Supreme Court and Songer Court of Appeals legal databases.
The majority of its 10,000 questions are multiple-choice, with 5,000 sourced from each database.
The questions are randomly selected from the test sets of the [Lawma tasks](https://huggingface.co/datasets/ricdomolm/lawma-tasks).
From a technical machine learning perspective, these tasks provide highly non-trivial classification problems where even the best models leave much room for improvement.
From a substantive legal perspective, efficient solutions to such classification problems have rich and important applications in legal research.

Homepage: https://github.com/socialfoundations/lawma