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.