beir/arguana

from hamu_tool.dataset import DataLoader

loader = DataLoader.load('beir/arguana')

for doc in loader.get_docs():
    print(doc.id, doc.text, doc.title)
    break

for query in loader.get_queries():
    print(query.id, query.text)
    break

for qrel in loader.get_qrels('[mode]'):
    print(qrel.qid, qrel.did, qrel.score)
    break

from hamu_tool.dataset import DataLoader

loader = DataLoader.load('beir/arguana')

doc = loader.get_doc('[did]')
print(doc)

query = loader.get_query('[qid]')
print(query)

qrel = loader.get_qrel('[mode]', '[qid]')
print(qrel)

@inproceedings{Wachsmuth2018Arguana,
  author = "Wachsmuth, Henning and Syed, Shahbaz and Stein, Benno",
  title = "Retrieval of the Best Counterargument without Prior Topic Knowledge",
  booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
  year = "2018",
  publisher = "Association for Computational Linguistics",
  location = "Melbourne, Australia",
  pages = "241--251",
  url = "http://aclweb.org/anthology/P18-1023"
}
@article{Thakur2021Beir,
  title = "BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models",
  author = "Thakur, Nandan and Reimers, Nils and Rücklé, Andreas and Srivastava, Abhishek and Gurevych, Iryna", 
  journal = "arXiv preprint arXiv:2104.08663",
  month = "4",
  year = "2021",
  url = "https://arxiv.org/abs/2104.08663",
}