2025
ACL
ACL 2025
Can information theory unravel the subtext in a Chekhovian short story?
Abstract
AbstractIn this study, we investigate whether information-theoretic measures such as surprisal can quantify the elusive notion of subtext in a Chekhovian short story. Specifically, we conduct a series of experiments for which we enrich the original text once with (different types of) meaningful glosses and once with fake glosses. For the different texts thus created, we calculate the surprisal values using two methods: using either a bag-of-words model or a large language model. We observe enrichment effects depending on the method, but no interpretable subtext effect.
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The Questioner
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Mathematics & Optimization and Natural Language Processing
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Keyword Pioneer
— subtext detection
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Understanding > Semantic Analysis
Mathematics & Optimization > Mathematics > Information Theory
Interdisciplinary > Linguistics > Computational Linguistics
Interdisciplinary > Linguistics > Semantics
Interdisciplinary > Science > Digital Humanities
Machine Learning > Optimization & Theory > Information Theory