README.md

---
task_categories:
- text-retrieval
task_ids:
- document-retrieval
config_names:
- corpus
tags:
- text-retrieval
dataset_info:
  - config_name: default
    features:
      - name: query-id
        dtype: string
      - name: corpus-id
        dtype: string
      - name: score
        dtype: float64
  - config_name: corpus
    features:
      - name: id
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
  - config_name: queries
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
configs:
  - config_name: default
    data_files:
      - split: test
        path: relevance.jsonl
  - config_name: corpus
    data_files:
      - split: corpus
        path: corpus.jsonl
  - config_name: queries
    data_files:
      - split: queries
        path: queries.jsonl
---

The dataset comprises 446 pairs of legal text excerpts and their corresponding plain English summaries, sourced from reputable websites dedicated to clarifying legal documents. The summaries have been manually reviewed for quality, ensuring that the data is clean and suitable for evaluating legal retrieval.

**Usage**
```
import datasets

# Download the dataset
queries = datasets.load_dataset("embedding-benchmark/LegalSummarization", "queries")
documents = datasets.load_dataset("embedding-benchmark/LegalSummarization", "corpus")
pair_labels = datasets.load_dataset("embedding-benchmark/LegalSummarization", "default")
```