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MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge

arXiv 1803.05223 ↗First posted 14 Mar 2018cs.CLcited by 30

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Abstract (arXiv)

We introduce a large dataset of narrative texts and questions about these texts, intended to be used in a machine comprehension task that requires reasoning using commonsense knowledge. Our dataset complements similar datasets in that we focus on stories about everyday activities, such as going to the movies or working in the garden, and that the questions require commonsense knowledge, or more specifically, script knowledge, to be answered. We show that our mode of data collection via crowdsourcing results in a substantial amount of such inference questions. The dataset forms the basis of a shared task on commonsense and script knowledge organized at SemEval 2018 and provides challenging test cases for the broader natural language understanding community.

Key facts. Cited by 30 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Mar 2018.

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Citing papers per year: 2021: 11; 2022: 6; 2023: 6; 2024: 5; 2025: 2.

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  1. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  2. 2021Comparing Test Sets with Item Response Theorycited by 57
  3. 2022UnifiedQA-v2: Stronger Generalization via Broader Cross-Format Trainingcited by 57
  4. 2023Benchmarks for Automated Commonsense Reasoning: A Surveycited by 40
  5. 2024Can LLM Generate Culturally Relevant Commonsense QA Data? Case Study in Indonesian and Sundanesecited by 36
  6. 2021Conversational Question Answering: A Surveycited by 31
  7. 2024Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once?cited by 30
  8. 2021Automatic Story Generation: Challenges and Attemptscited by 28
  9. 2021English Machine Reading Comprehension Datasets: A Surveycited by 26
  10. 2021What do Large Language Models Learn about Scripts?cited by 19
  11. 2022RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Questioncited by 17
  12. 2023Prompting with Pseudo-Code Instructionscited by 14
18 more
  1. 2023CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Biascited by 14
  2. 2022A Survey of Machine Narrative Reading Comprehension Assessmentscited by 10
  3. 2024mCSQA: Multilingual Commonsense Reasoning Dataset with Unified Creation Strategy by Language Models and Humanscited by 10
  4. 2021Language Model Augmented Relevance Scorecited by 7
  5. 2023Long-Tailed Question Answering in an Open Worldcited by 7
  6. 2022Probing Script Knowledge from Pre-Trained Modelscited by 4
  7. 2022A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehensioncited by 4
  8. 2021Encoding Explanatory Knowledge for Zero-shot Science Question Answeringcited by 3
  9. 2021Commonsense Knowledge in Word Associations and ConceptNetcited by 2
  10. 2023ScriptWorld: Text Based Environment For Learning Procedural Knowledgecited by 2
  11. 2025Cross-Asset Risk Management: Integrating LLMs for Real-Time Monitoring of Equity, Fixed Income, and Currency Marketscited by 2
  12. 2024LFED: A Literary Fiction Evaluation Dataset for Large Language Modelscited by 1
  13. 2021ReCAM@IITK at SemEval-2021 Task 4: BERT and ALBERT based Ensemble for Abstract Word Predictioncited by 0
  14. 2021ListReader: Extracting List-form Answers for Opinion Questionscited by 0
  15. 2022Using contradictions improves question answering systemscited by 0
  16. 2023Teach model to answer questions after comprehending the documentcited by 0
  17. 2024Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasetscited by 0
  18. 2025Adaptive Learning Systems: Personalized Curriculum Design Using LLM-Powered Analyticscited by 0