metadata

annotations_creators:
  - no-annotation
language:
  - fa
  - ru
  - zh
language_creators:
  - found
license:
  - odc-by
multilinguality:
  - multilingual
pretty_name: HC4
size_categories:
  - 1M<n<10M
source_datasets:
  - extended|c4
tags: []
task_categories:
  - text-retrieval
task_ids:
  - document-retrieval

Dataset Card for HC4

Dataset Description

Repository: https://github.com/hltcoe/HC4
Paper: https://arxiv.org/abs/2201.09992

Dataset Summary

HC4 is a suite of test collections for ad hoc Cross-Language Information Retrieval (CLIR), with Common Crawl News documents in Chinese, Persian, and Russian. The documents are Web pages from Common Crawl in Chinese, Persian, and Russian.

Languages

Chinese
Persian
Russian

Dataset Structure

Data Instances

Split	Documents
`fas` (Persian)	486K
`rus` (Russian)	4.7M
`zho` (Chinese)	646K

Data Fields

id: unique identifier for this document
cc_file: source file from connon crawl
time: extracted date/time from article
title: title extracted from article
text: extracted article body
url: source URL

Dataset Usage

Using 🤗 Datasets:

from datasets import load_dataset

dataset = load_dataset('neuclir/hc4')
dataset['fas'] # Persian documents
dataset['rus'] # Russian documents
dataset['zho'] # Chinese documents

Citation Information

@article{Lawrie2022HC4,
  author = {Dawn Lawrie and James Mayfield and Douglas W. Oard and Eugene Yang},
  title = {HC4: A New Suite of Test Collections for Ad Hoc CLIR},
  booktitle = {{Advances in Information Retrieval. 44th European Conference on IR Research (ECIR 2022)},
  year = {2022},
  month = apr,
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  site = {Stavanger, Norway},
  url = {https://arxiv.org/abs/2201.09992}
}