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parser_dataset
Parser training and evaluation data for multi-hop QA with long concatenated document contexts.
Derived from HotpotQA and 2WikiMultihopQA.
Contents
| Path | Split | Samples | Notes |
|---|---|---|---|
train/hotpotqa_train_process_emb-select_llm-unable.parquet |
train | HotpotQA processed train | VERL / ParserRLHFDataset format |
2wiki_val/eval_{N}.json |
eval | 128 per file | 2WikiMultihopQA, N documents per example |
hqa_val/eval_{N}.json |
eval | 128 per file | HotpotQA, N documents per example |
N ∈ {50, 100, 200, 400, 800, 1600, 3200, 6400}.
Load
from datasets import load_dataset
train = load_dataset("inNexus/parser_dataset", "train", split="train")
hqa_50 = load_dataset("inNexus/parser_dataset", "hqa_val", split="eval_50")
wiki_6400 = load_dataset("inNexus/parser_dataset", "2wiki_val", split="eval_6400")
Fields
Train parquet (consumed by ParserRLHFDataset): prompt, context, reward_model, data_source.
Eval JSON
hqa_val:context,input,answers,num_docs,index2wiki_val: same as above, plusis_ordered,is_reverse_ordered,min_distance,evidence_idx,level,type,id
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