This paper proposes a novel prompt engineering technique called Judgment of Thought (JoT) that is specifically tailored for binary logical reasoning tasks. JoT employs three roles$\unicode{x2014}$lawyer, prosecutor, and judge$\unicode{x2014}$to facilitate more reliable and accurate reasoning by the model. In this framework, the judge utilizes a high$\unicode{x2010}$level model, while the lawyer and prosecutor utilize low$\unicode{x2010}$level models. This structure helps the judge better understand the responses from both the lawyer and prosecutor, enabling a more accurate judgment. Experimental results on large language model (LLM) benchmark datasets, such as BigBenchHard and Winogrande, demonstrate that JoT outperforms existing methods, including Chain of Thought (CoT) and Self$\unicode{x2010}$Consistency (SC), in binary logical reasoning tasks. Additionally, in real$\unicode{x2010}$world tasks, such as Fake News Detection and SMS Spam Detection, JoT shows comparable or improved performance compared to existing techniques. JoT significantly enhances the accuracy and reliability of models in binary reasoning tasks and show potential for practical applicability across various domains. Future research should aim to further broaden the applicability of JoT and optimize its implementation for real$\unicode{x2010}$world problem$\unicode{x2010}$solving.

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His psychiatric training was at Rockland State Hospital (N.Y.), 1932-4. Until 1941 he held several fellowships at Yale University, Laboratory of Neurophysiology, on activity of the central nervous system, becoming Assistant Professor 1940-1. From 1941 to 1952 he was Professor of Psychiatry and Physiology and Neurophysiologist at the University of Illinois. Since 1952 he has been staff member of the Research Laboratory of Electronics at Massachusetts Institute of Technology. He is the author of numerous articles on functional organization of the brain, and on facilitation, extinction and functional organisation of the cerebral cortex. SUMMARY VENN diagrams, with a jot in every space for all cases in which given logical functions are true, picture their truth tables. These symbols serve as arguments in similar expressions that use similar symbols for functions of functions. When jots appear fortuitously with given probabilities or frequencies, the Venn diagram can be written with l's for fixed jots, O's for fixed absence, and p's for fortuitous jots. Any function is realizable by many synaptic diagrams of formal neurons of specified threshold, and the fortuitous jots of their symbols can be made to signify a perturbation of threshold in an appropriate synaptic diagram. Nets of these neurons with common inputs embody hierarchies of functions, each of which can be reduced to input-output functions pictured in their truth tables.