annotate-relevance / constants.py
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ALL_METRICS = [
"ndcg_cut_10",
"ndcg_cut_5",
"ndcg_cut_15",
"ndcg_cut_20",
"ndcg_cut_30",
"ndcg_cut_100",
"ndcg_cut_200",
"ndcg_cut_500",
"ndcg_cut_1000",
"map",
"P_5",
"P_10",
"P_15",
"P_20",
"P_30",
"P_100",
"P_200",
"P_500",
"P_1000",
"recall_5",
"recall_10",
"recall_15",
"recall_20",
"recall_30",
"recall_100",
"recall_200",
"recall_500",
"recall_1000",
"recip_rank",
"set_recall",
"set_P",
"set_F",
"num_rel_ret",
"num_ret",
"num_rel",
"num_q",
"num_rel",
"num_rel_ret"
"Rprec",
"bpref",
"iprec_at_recall_0.00",
"iprec_at_recall_0.10",
"iprec_at_recall_0.20",
"iprec_at_recall_0.30",
"iprec_at_recall_0.40",
"iprec_at_recall_0.50",
"iprec_at_recall_0.60",
"iprec_at_recall_0.70",
"iprec_at_recall_0.80",
"iprec_at_recall_0.90",
"iprec_at_recall_1.00",
]
BEIR = [
"msmarco",
"trec-covid",
"nf_corpus",
"bioasq",
"nq",
"hotpotqa",
"fiqa",
"signal1m",
"trec-news",
"robust04",
"arguana",
"webis-touche2020",
"cqadupstack",
"quora",
"dbpedia-entity",
"scidocs",
"fever",
"climate-fever",
"scifact",
]
IR_DATASETS = [
"antique",
"aol_ia",
"aquaint",
"argsme",
"c4",
"car",
"clinicaltrials",
"clirmatrix",
"clueweb09",
"clueweb12",
"codec",
"cord19",
"cranfield",
"disks45",
"dpr_w100",
"codesearchnet",
"gov",
"gov2",
"highwire",
"istella22",
"kilt",
"lotte",
"medline",
"mmarco",
"mr_tydi",
"msmarco_document",
"msmarco_document_v2",
"msmarco_passage",
"msmarco_passage_v2",
"msmarco_qna",
"neumarco",
"nfcorpus",
"natural_questions",
"nyt",
"pmc",
"touche_image",
"touche",
"trec_arabic",
"trec_mandarin",
"trec_spanish",
"trec_robust04",
"trec_tot",
"tripclick",
"tweets2013_ia",
"vaswani",
"wapo",
"wikiclir",
"wikir",
"trec_fair",
"trec_cast",
"hc4",
"neuclir",
"sara",
]
LOCAL_DATASETS = [
"gooaq_technical",
"codesearch_py",
]
ALL_DATASETS = ["", "custom"] + LOCAL_DATASETS + BEIR + IR_DATASETS