Datasets:

Daeyongkwon98
/

SAFE-Verified-MultiHopQA

language:
  - en
task_categories:
  - question-answering
pretty_name: SAFE-Verified-MultiHopQA
configs:
  - config_name: 2wiki
    data_files:
      - split: train
        path: data/2wiki/train.parquet
      - split: validation
        path: data/2wiki/validation.parquet
  - config_name: hotpotqa
    data_files:
      - split: train
        path: data/hotpotqa/train.parquet
      - split: validation
        path: data/hotpotqa/validation.parquet
  - config_name: musique
    data_files:
      - split: train
        path: data/musique/train.parquet
      - split: validation
        path: data/musique/validation.parquet

SAFE-Verified-MultiHopQA

Paper | Project Page

Overview

SAFE-Verified-MultiHopQA is released with the EMNLP 2026 paper SAFE: An LLM-as-Verifier Framework for Evidence-Grounded Multi-Hop Reasoning. It provides Knowledge Graph (KG) based, cleaned versions of three multi-hop question-answering benchmarks:

2WikiMultiHopQA (2wiki)
HotpotQA (hotpotqa)
MuSiQue (musique)

SAFE uses KG-grounded verification to identify questions with invalid or ungrounded reasoning. This release removes the questions identified as wrong by SAFE from the original train and development (val) splits.

SAFE retains the original columns of the datasets and provides two standardized passage fields. gt_passages is a list of ground-truth passages, and retrieved_passages is a list of 10 retrieved passages that combines ground-truth passages with distractor passages in random order. Both fields are converted from the source dataset formats into a unified paragraph-level list representation.

🔍 Why verification is needed?

Through KG-based verification, we identified and verified the following errors in existing benchmarks, which account for up to 14% of instances in each split.

Issue type	uestion	Answer	Passage (key evidence)
Incorrect answer	Was there any debate about the voting process in the state where Atwater Congregational Church is located?	a motion was made contesting Ohio's electoral votes	The passage mentions a motion about Ohio's electoral votes, but does not provide the required yes/no answer about a debate over the voting process.
Ambiguous question	Who is a cast member of the show in which Jana Brandner is a character?	Valerie Niehaus	The passages support multiple answers: both Valerie Niehaus and Sven Koller are cast members of Verbotene Liebe.
Insufficient context	What dynasty gave birth to the country in which the House of Luxembourg was located?	the Carolingian family	The passages associate the House of Luxembourg with Luxembourg but never identify the dynasty that founded Luxembourg.

Download and use

from datasets import load_dataset

data = load_dataset(
    "Daeyongkwon98/SAFE-Verified-MultiHopQA",
    "2wiki", # "hotpotqa", "musique"
)

train = data["train"]
validation = data["validation"]

Dataset splits and sizes

train is the filtered version of the original training split. validation is the filtered version of the source development (dev) split.

Dataset	Split	Original rows	Filtered by SAFE	Final rows	Error (%)
`2wiki`	train	167,454	7,452	160,002	4.45%
`2wiki`	validation	12,576	901	11,675	7.16%
`hotpotqa`	train	90,447	2,377	88,070	2.63%
`hotpotqa`	validation	7,345	227	7,118	3.09%
`musique`	train	19,902	2,149	17,753	10.80%
`musique`	validation	2,412	342	2,070	14.18%
Total	—	300,136	13,448	286,688	4.48%

Example Data

{
  "id": "13f5ad2c088c11ebbd6fac1f6bf848b6",
  "type": "bridge_comparison",
  "question": "Are director of film Move (1970 Film) and director of film Méditerranée (1963 Film) from the same country?",
  "answer": "no",
  "retrieved_passages": "[p1, p2, ..., p10]",
  "gt_passages": "[p2, p10]"
}

Data Information

2WikiMultiHopQA

Column	Available in	Description
`id`	Train, validation	Unique example identifier; renamed from the source `_id` in train.
`type`	Train, validation	Source question/reasoning category.
`question`	Train, validation	Multi-hop natural-language question.
`context`	Train, validation	Serialized source context.
`entity_ids`	Train	2Wiki entity identifiers.
`supporting_facts`	Train, validation	Supporting facts needed to answer the question.
`evidences`	Train, validation	Knowledge-graph evidence triples.
`answer`	Train, validation	Reference answer.
`evidences_id`	Train	Knowledge-graph evidence triples represented with IDs.
`answer_id`	Train	Answer entity ID, when present.
`retrieved_passages`	Train, validation	Standardized paragraph-level list of ten retrieved passages, containing ground-truth passages and distractors.
`answer_list`	Validation	Answer aliases provided by the source validation data.
`gt_passages`	Train, validation	Standardized paragraph-level list of ground-truth passages.

HotpotQA

Column	Available in	Description
`id`	Train, validation	Unique example identifier.
`question`	Train, validation	Multi-hop natural-language question.
`answer`	Train, validation	Reference answer.
`type`	Train, validation	Source question/reasoning category.
`level`	Train, validation	Source difficulty level.
`supporting_facts`	Train, validation	Supporting facts needed to answer the question.
`context`	Train, validation	Serialized source context.
`retrieved_passages`	Train, validation	Standardized paragraph-level list of ten retrieved passages, containing ground-truth passages and distractors.
`gt_passages`	Train, validation	Standardized paragraph-level list of ground-truth passages.
`answer_list`	Validation	Answer aliases provided by the source validation data.

MuSiQue

Column	Available in	Description
`id`	Train, validation	Unique example identifier.
`paragraphs`	Train, validation	Serialized candidate paragraphs.
`question`	Train, validation	Multi-hop natural-language question.
`question_decomposition`	Train, validation	Decomposition into component reasoning questions.
`answer`	Train, validation	Reference answer.
`answer_aliases`	Train, validation	Acceptable answer aliases.
`answerable`	Train, validation	Source answerability indicator.
`retrieved_passages`	Train, validation	Standardized paragraph-level list of ten retrieved passages, containing ground-truth passages and distractors.
`gt_passages`	Train, validation	Standardized paragraph-level list of ground-truth passages.
`answer_list`	Validation	Answer aliases provided by the source validation data.

Citation

If you find our datasets useful, please cite our paper!

@article{kwon2026safe,
  title={SAFE: An LLM-as-Verifier Framework for Evidence-Grounded Multi-Hop Reasoning},
  author={Kwon, Daeyong and Yoon, Soyoung and Hwang, Seung-won},
  journal={arXiv preprint arXiv:2604.01993},
  year={2026}
}

If you have any questions, feel free to contact daeyongkwon@snu.ac.kr.