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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Column(/metadata/supporting_facts/[]/[]) changed from string to number in row 0
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 145, in _generate_tables
                  dataset = json.load(f)
                File "/usr/local/lib/python3.9/json/__init__.py", line 293, in load
                  return loads(fp.read(),
                File "/usr/local/lib/python3.9/json/__init__.py", line 346, in loads
                  return _default_decoder.decode(s)
                File "/usr/local/lib/python3.9/json/decoder.py", line 340, in decode
                  raise JSONDecodeError("Extra data", s, end)
              json.decoder.JSONDecodeError: Extra data: line 2 column 1 (char 223)
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head
                  return _examples_to_batch(list(self.take(n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__
                  yield from islice(self.ex_iterable, self.n)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
                  for key, pa_table in self.generate_tables_fn(**self.kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 148, in _generate_tables
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 122, in _generate_tables
                  pa_table = paj.read_json(
                File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/metadata/supporting_facts/[]/[]) changed from string to number in row 0

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

Data Description

Dataset Summary

All the 16 benchmarked datasets in Cocktail are listed in the following table.

Dataset Raw Website Cocktail Website Cocktail-Name md5 for Processed Data Domain Relevancy # Test Query # Corpus
MS MARCO Homepage Homepage msmarco 985926f3e906fadf0dc6249f23ed850f Misc. Binary 6,979 542,203
DL19 Homepage Homepage dl19 d652af47ec0e844af43109c0acf50b74 Misc. Binary 43 542,203
DL20 Homepage Homepage dl20 3afc48141dce3405ede2b6b937c65036 Misc. Binary 54 542,203
TREC-COVID Homepage Homepage trec-covid 1e1e2264b623d9cb7cb50df8141bd535 Bio-Medical 3-level 50 128,585
NFCorpus Homepage Homepage nfcorpus 695327760647984c5014d64b2fee8de0 Bio-Medical 3-level 323 3,633
NQ Homepage Homepage nq a10bfe33efdec54aafcc974ac989c338 Wikipedia Binary 3,446 104,194
HotpotQA Homepage Homepage hotpotqa 74467760fff8bf8fbdadd5094bf9dd7b Wikipedia Binary 7,405 111,107
FiQA-2018 Homepage Homepage fiqa 4e1e688539b0622630fb6e65d39d26fa Finance Binary 648 57,450
TouchΓ©-2020 Homepage Homepage webis-touche2020 d58ec465ccd567d8f75edb419b0faaed Misc. 3-level 49 101,922
CQADupStack Homepage Homepage cqadupstack d48d963bc72689c765f381f04fc26f8b StackEx. Binary 1,563 39,962
DBPedia Homepage Homepage dbpedia-entity 43292f4f1a1927e2e323a4a7fa165fc1 Wikipedia 3-level 400 145,037
SCIDOCS Homepage Homepage scidocs 4058c0915594ab34e9b2b67f885c595f Scientific Binary 1,000 25,259
FEVER Homepage Homepage fever 98b631887d8c38772463e9633c477c69 Wikipedia Binary 6,666 114,529
Climate-FEVER Homepage Homepage climate-fever 5734d6ac34f24f5da496b27e04ff991a Wikipedia Binary 1,535 101,339
SciFact Homepage Homepage scifact b5b8e24ccad98c9ca959061af14bf833 Scientific Binary 300 5,183
NQ-UTD Homepage Homepage nq-utd 2e12e66393829cd4be715718f99d2436 Misc. 3-level 80 800

Dataset Structure

.
β”œβ”€β”€ corpus # * documents
β”‚   β”œβ”€β”€ human.jsonl # * human-written corpus
β”‚   └── llama-2-7b-chat-tmp0.2.jsonl # * llm-generated corpus
β”œβ”€β”€ qrels
β”‚   └── test.tsv # * relevance for queries
└── queries.jsonl  # * quereis

All Cocktail datasets must contain a humman-written corpus, a LLM-generated corpus, queries and qrels. They must be in the following format:

  • corpus: a .jsonl file (jsonlines) that contains a list of dictionaries, each with three fields _id with unique document identifier, title with document title (optional) and text with document paragraph or passage. For example: {"_id": "doc1", "title": "title", "text": "text"}
  • queries file: a .jsonl file (jsonlines) that contains a list of dictionaries, each with two fields _id with unique query identifier and text with query text. For example: {"_id": "q1", "text": "q1_text"}
  • qrels file: a .tsv file (tab-seperated) that contains three columns, i.e. the query-id, corpus-id and score in this order. Keep 1st row as header. For example: q1 doc1 1

Cite as:

@article{cocktail,
  title={Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration},
  author={Dai, Sunhao and Liu, Weihao and Zhou, Yuqi and Pang, Liang and Ruan, Rongju and Wang, Gang and Dong, Zhenhua and Xu, Jun and Wen, Ji-Rong},
  journal={Findings of the Association for Computational Linguistics: ACL 2024},
  year={2024}
}

@article{dai2024neural,
  title={Neural Retrievers are Biased Towards LLM-Generated Content},
  author={Dai, Sunhao and Zhou, Yuqi and Pang, Liang and Liu, Weihao and Hu, Xiaolin and Liu, Yong and Zhang, Xiao and Wang, Gang and Xu, Jun},
  journal={Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year={2024}
}
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