Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Sub-tasks:
document-retrieval
Size:
< 1K
Tags:
text-retrieval
File size: 1,552 Bytes
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---
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 descriptions of 197 Supreme Court of India statutes, designed to facilitate the retrieval of relevant prior statutes for given legal situations. It includes 50 queries, each outlining a specific scenario. We include this dataset in the benchmark because the documents are reasonably challenging, the queries are non-synthetic, and the labels are of high quality.
**Usage**
```
import datasets
# Download the dataset
queries = datasets.load_dataset("embedding-benchmark/AILAStatutes", "queries")
documents = datasets.load_dataset("embedding-benchmark/AILAStatutes", "corpus")
pair_labels = datasets.load_dataset("embedding-benchmark/AILAStatutes", "default")
``` |