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""" |
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Simple script to pre-download and JSON-serialize the query-relations of MTEB datasets, since the `mteb` library requires us to download the full dataset to get just the qrels, and that's slow to do every time we want just qrels. |
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""" |
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import json |
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from pathlib import Path |
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import mteb |
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from tqdm.auto import tqdm |
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names = [ |
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'ArguAna', |
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'CQADupstackAndroidRetrieval', |
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'CQADupstackEnglishRetrieval', |
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'CQADupstackGamingRetrieval', |
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'CQADupstackGisRetrieval', |
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'CQADupstackMathematicaRetrieval', |
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'CQADupstackPhysicsRetrieval', |
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'CQADupstackProgrammersRetrieval', |
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'CQADupstackStatsRetrieval', |
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'CQADupstackTexRetrieval', |
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'CQADupstackUnixRetrieval', |
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'CQADupstackWebmastersRetrieval', |
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'CQADupstackWordpressRetrieval', |
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'ClimateFEVER', |
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'DBPedia', |
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'FEVER', |
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'FiQA2018', |
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'HotpotQA', |
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'MSMARCO', |
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'NFCorpus', |
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'NQ', |
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'QuoraRetrieval', |
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'SCIDOCS', |
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'SciFact', |
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'TRECCOVID', |
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'Touche2020' |
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] |
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out_path = Path(__file__) |
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def load_mteb_qrels(task_name: str) -> dict: |
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split_name = "dev" if task_name == "MSMARCO" else "test" |
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task_obj = mteb.MTEB(tasks=[mteb.get_task(task_name, languages=["en"])]).tasks[0] |
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task_obj.load_data(eval_splits=[split_name]) |
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qrels = task_obj.relevant_docs[split_name] |
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return qrels |
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for name in tqdm(names, desc="downloading qrels", unit="dataset"): |
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qrel = load_mteb_qrels(name) |
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out_file_path = (out_path / f"{name}.json") |
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out_file_path.write_text(json.dumps(qrel, indent=2, sort_keys=True)) |
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