Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Sub-tasks:
document-retrieval
Languages:
English
Size:
< 1K
Tags:
text-retrieval
File size: 1,724 Bytes
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---
language:
- en
multilinguality:
- monolingual
task_categories:
- text-retrieval
source_datasets:
- https://zenodo.org/records/4063986
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
splits:
- name: test
num_examples: 217
- config_name: corpus
features:
- name: _id
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: corpus
num_examples: 82
- config_name: queries
features:
- name: _id
dtype: string
- name: text
dtype: string
splits:
- name: queries
num_examples: 50
configs:
- config_name: default
data_files:
- split: test
path: qrels/test.jsonl
- config_name: corpus
data_files:
- split: corpus
path: corpus.jsonl
- config_name: queries
data_files:
- split: queries
path: queries.jsonl
---
**AILA_statutes**
- Original link: https://zenodo.org/records/4063986
- This dataset is structured for the task of identifying the most relevant statutes for a given situation.
- The query set comprises 50 queries, each describing a specific situation.
- The corpus set consists of the title and description of statutes.
**Usage**
```
import datasets
# Download the dataset
queries = datasets.load_dataset("mteb/AILA_statutes", "queries")
documents = datasets.load_dataset("mteb/AILA_statutes", "corpus")
pair_labels = datasets.load_dataset("mteb/AILA_statutes", "default")
``` |