# IslamicPCQA: A Dataset for Persian Multi-hop Complex Question Answering in Islamic Text Resources

arXiv: https://arxiv.org/abs/2304.11664 · HTML: https://mlsanity.com/paper/2304.11664/

## Key facts

- Cited by 1 papers 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 (most cited first, 21 of 21)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering](https://mlsanity.com/paper/1809.09600/) (2018)
- [TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension](https://mlsanity.com/paper/1705.03551/) (2017)
- [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://mlsanity.com/paper/1909.11942/) (2019)
- [mT5: A massively multilingual pre-trained text-to-text transformer](https://mlsanity.com/paper/2010.11934/) (2020)
- [Know What You Don't Know: Unanswerable Questions for SQuAD](https://mlsanity.com/paper/1806.03822/) (2018)
- [On the Cross-lingual Transferability of Monolingual Representations](https://mlsanity.com/paper/1910.11856/) (2019)
- [MLQA: Evaluating Cross-lingual Extractive Question Answering](https://mlsanity.com/paper/1910.07475/) (2019)
- [Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases](https://mlsanity.com/paper/2011.07743/) (2020)
- [ParsBERT: Transformer-based Model for Persian Language Understanding](https://mlsanity.com/paper/2005.12515/) (2020)
- [Question Answering with Subgraph Embeddings](https://mlsanity.com/paper/1406.3676/) (2014)
- [Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion](https://mlsanity.com/paper/1910.03262/) (2019)
- [ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters](https://mlsanity.com/paper/1809.09528/) (2018)
- [RuBQ: A Russian Dataset for Question Answering over Wikidata](https://mlsanity.com/paper/2005.10659/) (2020)
- [PQuAD: A Persian Question Answering Dataset](https://mlsanity.com/paper/2202.06219/) (2022)
- [ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation](https://mlsanity.com/paper/2103.07771/) (2021)
- [VANiLLa : Verbalized Answers in Natural Language at Large Scale](https://mlsanity.com/paper/2105.11407/) (2021)
- [A Chinese Multi-type Complex Questions Answering Dataset over Wikidata](https://mlsanity.com/paper/2111.06086/) (2021)
- [PerCQA: Persian Community Question Answering Dataset](https://mlsanity.com/paper/2112.13238/) (2021)
- [PeCoQ: A Dataset for Persian Complex Question Answering over Knowledge Graph](https://mlsanity.com/paper/2106.14167/) (2021)

## Built on by (most cited first, 1 of 1)

- [Building a Rich Dataset to Empower the Persian Question Answering Systems](https://mlsanity.com/paper/2412.20212/) (2024)

## 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