IslamicPCQA: A Dataset for Persian Multi-hop Complex Question Answering in Islamic Text Resources
Not on the map. Why?
Abstract (arXiv)
Nowadays, one of the main challenges for Question Answering Systems is to answer complex questions using various sources of information. Multi-hop questions are a type of complex questions that require multi-step reasoning to answer. In this article, the IslamicPCQA dataset is introduced. This is the first Persian dataset for answering complex questions based on non-structured information sources and consists of 12,282 question-answer pairs extracted from 9 Islamic encyclopedias. This dataset has been created inspired by the HotpotQA English dataset approach, which was customized to suit the complexities of the Persian language. Answering questions in this dataset requires more than one paragraph and reasoning. The questions are not limited to any prior knowledge base or ontology, and to provide robust reasoning ability, the dataset also includes supporting facts and key sentences. The prepared dataset covers a wide range of Islamic topics and aims to facilitate answering complex Persian questions within this subject matter
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 23 Apr 2023.
Builds on
21 of 38 references.
References · 21
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
- 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
- 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
- 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
- 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,554
- 2019On the Cross-lingual Transferability of Monolingual Representationscited by 578
- 2019MLQA: Evaluating Cross-lingual Extractive Question Answeringcited by 340
- 2020Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Basescited by 171
- 2020ParsBERT: Transformer-based Model for Persian Language Understandingcited by 93
- 2014Question Answering with Subgraph Embeddingscited by 58
9 more
- 2019Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansioncited by 42
- 2018ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusterscited by 29
- 2020RuBQ: A Russian Dataset for Question Answering over Wikidatacited by 14
- 2022PQuAD: A Persian Question Answering Datasetcited by 14
- 2021ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversationcited by 12
- 2021VANiLLa : Verbalized Answers in Natural Language at Large Scalecited by 5
- 2021A Chinese Multi-type Complex Questions Answering Dataset over Wikidatacited by 5
- 2021PerCQA: Persian Community Question Answering Datasetcited by 5
- 2021PeCoQ: A Dataset for Persian Complex Question Answering over Knowledge Graphcited by 4
Built on by
Citing papers per year: 2024: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
- 2025FARSIQA: Faithful and Advanced RAG System for Islamic Question Answering
- 2024MoreHopQA: More Than Multi-hop Reasoning
- 2023MarkQA: A large scale KBQA dataset with numerical reasoning
- 2026PARSE: An Open-Domain Reasoning Question Answering Benchmark for Persian
- 2024ComplexTempQA:A 100m Dataset for Complex Temporal Question Answering
- 2022A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
- 2026Islamic Large Language Models: From Knowledge Acquisition to Trustworthy and Hallucination-Resistant AI
- 2024Table Question Answering for Low-resourced Indic Languages