IslamicPCQA: A Dataset for Persian Multi-hop Complex Question Answering in Islamic Text Resources
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
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
FARSIQA: Faithful and Advanced RAG System for Islamic Question Answering
The advent of Large Language Models (LLMs) has revolutionized Natural Language Processing, yet their application in high-stakes, specialized domains like religious question answering is hindered by challenges like halluc…
Question AnsweringA Knowledge-based Approach for Answering Complex Questions in Persian
Research on open-domain question answering (QA) has a long tradition. A challenge in this domain is answering complex questions (CQA) that require complex inference methods and large amounts of knowledge. In low resource…
Open-Domain Question AnsweringQuestion AnsweringPeCoQ: A Dataset for Persian Complex Question Answering over Knowledge Graph
Question answering systems may find the answers to users' questions from either unstructured texts or structured data such as knowledge graphs. Answering questions using supervised learning approaches including deep lear…
Knowledge GraphsQuestion AnsweringA Method for Multi-Hop Question Answering on Persian Knowledge Graph
Question answering systems are the latest evolution in information retrieval technology, designed to accept complex queries in natural language and provide accurate answers using both unstructured and structured knowledg…
Graph Question AnsweringInformation RetrievalKnowledge GraphsMulti-hop Question Answering+2PQuAD: A Persian Question Answering Dataset
We present Persian Question Answering Dataset (PQuAD), a crowdsourced reading comprehension dataset on Persian Wikipedia articles. It includes 80,000 questions along with their answers, with 25% of the questions being ad…
ArticlesDiversityQuestion AnsweringReading Comprehension