{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/modeling-naive-psychology-of-characters-in","title":"Modeling Naive Psychology of Characters in Simple Commonsense Stories","arxiv_id":"1805.06533","date":"2018-05-16","proceeding":"ACL 2018 7","authors":["Hannah Rashkin","Antoine Bosselut","Maarten Sap","Kevin Knight","Yejin Choi"],"abstract":"Understanding a narrative requires reading between the lines and reasoning\nabout the unspoken but obvious implications about events and people's mental\nstates - a capability that is trivial for humans but remarkably hard for\nmachines. To facilitate research addressing this challenge, we introduce a new\nannotation framework to explain naive psychology of story characters as\nfully-specified chains of mental states with respect to motivations and\nemotional reactions. Our work presents a new large-scale dataset with rich\nlow-level annotations and establishes baseline performance on several new\ntasks, suggesting avenues for future research.","url_abs":"http://arxiv.org/abs/1805.06533v1","url_pdf":"http://arxiv.org/pdf/1805.06533v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"emotion-classification","task_name":"Emotion Classification"}],"methods":[],"datasets_introduced":[{"slug":"story-commonsense","name":"Story Commonsense","full_name":""}],"methods_introduced":[],"results":[{"leaderboard":"/sota/emotion-classification-on-rocstories","task":"Emotion Classification","dataset":"ROCStories","model":"NPN + Explanation Training","rank_in_archive_order":2,"of":2,"metrics":{"F1":"30.29"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1805.06533","atlas_url":"https://app.syntology.ai/?focus=1805.06533","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}