ComplexTempQA:A 100m Dataset for Complex Temporal Question Answering
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Abstract (arXiv)
We introduce textscComplexTempQA,footnoteDataset and code available at: https://github.com/DataScienceUIBK/ComplexTempQA a large-scale dataset consisting of over 100 million question-answer pairs designed to tackle the challenges in temporal question answering. textscComplexTempQA significantly surpasses existing benchmarks in scale and scope. Utilizing Wikipedia and Wikidata, the dataset covers questions spanning over two decades and offers an unmatched scale. We introduce a new taxonomy that categorizes questions as textitattributes, textitcomparisons, and textitcounting questions, revolving around events, entities, and time periods, respectively. A standout feature of textscComplexTempQA is the high complexity of its questions, which demand reasoning capabilities for answering such as across-time comparison, temporal aggregation, and multi-hop reasoning involving temporal event ordering and entity recognition. Additionally, each question is accompanied by detailed metadata, including specific time scopes, allowing for comprehensive evaluation of temporal reasoning abilities of large language models.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 20 of its 38 references that are in the map. First posted on arXiv 7 Jun 2024.
Builds on
20 of 38 references.
References · 20
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8 more
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Citing papers per year: 2024: 1; 2025: 4; 2026: 1.
6 papers.
- 2025It's High Time: A Survey of Temporal Question Answeringcited by 12
- 2025DeAR: Dual-Stage Document Reranking with Reasoning Agents via LLM Distillationcited by 11
- 2024RASTeR: Robust, Agentic, and Structured Temporal Reasoningcited by 2
- 2025HistoryBankQA: Multilingual Temporal Question Answering on Historical Eventscited by 1
- 2026Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understandingcited by 1
- 2025Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Modelscited by 0
- 2026Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understanding9 Aug 2026
- 2025HistoryBankQA: Multilingual Temporal Question Answering on Historical Events16 Sep 2025
- 2025DeAR: Dual-Stage Document Reranking with Reasoning Agents via LLM Distillation23 Aug 2025
- 2025Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models4 Aug 2025
- 2025It's High Time: A Survey of Temporal Question Answering26 May 2025
- 2024RASTeR: Robust, Agentic, and Structured Temporal Reasoning27 Jun 2024
Similar, not cited
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- 2022A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
- 2025A Question Answering Dataset for Temporal-Sensitive Retrieval-Augmented Generation
- 2023TempTabQA: Temporal Question Answering for Semi-Structured Tables
- 2023Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning
- 2025RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models
- 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement
- 2022TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs
- 2022Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases