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HandWiki. Winograd Schema Challenge. Encyclopedia. Available online: https://encyclopedia.pub/entry/29735 (accessed on 03 October 2026).
HandWiki. Winograd Schema Challenge. Encyclopedia. Available at: https://encyclopedia.pub/entry/29735. Accessed October 03, 2026.
HandWiki. "Winograd Schema Challenge" Encyclopedia, https://encyclopedia.pub/entry/29735 (accessed October 03, 2026).
HandWiki. (2022, October 18). Winograd Schema Challenge. In Encyclopedia. https://encyclopedia.pub/entry/29735
HandWiki. "Winograd Schema Challenge." Encyclopedia. Web. 18 October, 2022.
Winograd Schema Challenge
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The content is sourced from: https://handwiki.org/wiki/Winograd_schema_challenge

The Winograd schema challenge (WSC) is a test of machine intelligence proposed by Hector Levesque, a computer scientist at the University of Toronto. Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what are called Winograd schemas, named after Terry Winograd, professor of computer science at Stanford University. On the surface, Winograd schema questions simply require the resolution of anaphora: the machine must identify the antecedent of an ambiguous pronoun in a statement. This makes it a task of natural language processing, but Levesque argues that for Winograd schemas, the task requires the use of knowledge and commonsense reasoning. Nuance Communications announced in July 2014 that it would sponsor an annual WSC competition, with a prize of $25,000 for the best system that could match human performance. However, the prize is no longer offered.

natural language multiple-choice test machine intelligence

References

  1. Turing, Alan (October 1950). "Computing Machinery and Intelligence". Mind LIX (236): 433–460. doi:10.1093/mind/LIX.236.433. http://phil415.pbworks.com/f/TuringComputing.pdf. Retrieved 28 October 2014. 
  2. Levesque, Hector; Davis, Ernest; Morgenstern, Leora (2012). "The Winograd Schema Challenge". http://www.aaai.org/ocs/index.php/KR/KR12/paper/download/4492/4924. Retrieved 29 October 2014. 
  3. Levesque, H. J. (2014). "On our best behaviour". Artificial Intelligence 212: 27–35. doi:10.1016/j.artint.2014.03.007.  https://dx.doi.org/10.1016%2Fj.artint.2014.03.007
  4. Michael, Julian (18 May 2015). The Theory of Correlation Formulas and Their Application to Discourse Coherence. UT Digital Repository. p. 6. 
  5. Winograd, Terry (Jan 1972). "Understanding Natural Language". Cognitive Psychology 3 (1): 1–191. doi:10.1016/0010-0285(72)90002-3. http://ac.els-cdn.com/0010028572900023/1-s2.0-0010028572900023-main.pdf?_tid=60a02632-63c1-11e4-81b8-00000aacb35f&acdnat=1415064473_e5b480b8f467ac1be8bdfa3354ba6608. Retrieved 4 November 2014. 
  6. Davis, Ernest. "A Collection of Winograd Schemas". NYU. https://www.cs.nyu.edu/davise/papers/WS.html. Retrieved 30 October 2014. 
  7. Sakaguchi, Keisuke; Ronan Le Bras; Bhagavatula, Chandra; Choi, Yejin (2019). "WinoGrande: An Adversarial Winograd Schema Challenge at Scale". arXiv:1907.10641 [cs.CL]. //arxiv.org/archive/cs.CL
  8. Boguslavsky, I.M.; Frolova, T.I.; Iomdin, L.L.; Lazursky, A.V.; Rygaev, I.P.; Timoshenko, S.P. (2019). "Knowledge-based approach to Winograd Schema Challenge". Proceedings of the International Conference of Computational Linguistics and Intellectual Technologies (Moscow). http://www.dialog-21.ru/media/4589/boguslavskyimplusetal-111.pdf. "The prize could not be awarded to anybody. Most of the participants showed a result close to the random choice or even worse. The second competition scheduled for 2018 was canceled due to the lack of prospective participants.". 
  9. "Winograd Schema Challenge". http://commonsensereasoning.org/winograd.html. Retrieved 24 January 2020. 
  10. "AAAI 2015 Spring Symposia". http://www.aaai.org/Symposia/Spring/sss15symposia.php#ss04. Retrieved 1 January 2015. 
  11. Davis, Ernest; Morgenstern, Leora; Ortiz, Charles (Fall 2017). "The First Winograd Schema Challenge at IJCAI-16". AI Magazine. http://www.aimagazine-digital.org/aimagazine/fall_2017?sub_id=TUUUqmoUzKCg&pg=99#pg99. 
  12. Liu, Quan; Jiang, Hui; Ling, Zhen-Hua; Zhu, Xiaodan; Wei, Si; Hu, Yu (2016). "Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge". arXiv:1611.04146 [cs.AI]. //arxiv.org/archive/cs.AI
  13. Liu, Quan; Jiang, Hui; Evdokimov, Andrew; Ling, Zhen-Hua; Zhu, Xiaodan; Wei, Si; Hu, Yu (2017). "Cause-Effect Knowledge Acquisition and Neural Association Model for Solving A Set of Winograd Schema Problems". Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence: 2344–2350. doi:10.24963/ijcai.2017/326. ISBN 9780999241103. https://www.ijcai.org/Proceedings/2017/326. 
  14. Trinh, Trieu H.; Le, Quoc V. (2019-09-26). "A Simple Method for Commonsense Reasoning". arXiv:1806.02847 [cs.AI]. //arxiv.org/archive/cs.AI
  15. Brown, Tom B.; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; Neelakantan, Arvind; Shyam, Pranav; Sastry, Girish; Askell, Amanda; Agarwal, Sandhini; Herbert-Voss, Ariel; Krueger, Gretchen; Henighan, Tom; Child, Rewon; Ramesh, Aditya; Ziegler, Daniel M.; Wu, Jeffrey; Winter, Clemens; Hesse, Christopher; Chen, Mark; Sigler, Eric; Litwin, Mateusz; Gray, Scott; Chess, Benjamin; Clark, Jack; Berner, Christopher; McCandlish, Sam; Radford, Alec; et al. (2020). "Language Models are Few-Shot Learners". arXiv:2005.14165 [cs.CL]. //arxiv.org/archive/cs.CL
  16. "GLUE Benchmark". https://gluebenchmark.com/. Retrieved 30 July 2019. 
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