{"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/whodunnit-crime-drama-as-a-case-for-natural","title":"Whodunnit? Crime Drama as a Case for Natural Language Understanding","arxiv_id":"1710.11601","date":"2017-10-31","proceeding":"TACL 2018 1","authors":["Lea Frermann","Shay B. Cohen","Mirella Lapata"],"abstract":"In this paper we argue that crime drama exemplified in television programs\nsuch as CSI:Crime Scene Investigation is an ideal testbed for approximating\nreal-world natural language understanding and the complex inferences associated\nwith it. We propose to treat crime drama as a new inference task, capitalizing\non the fact that each episode poses the same basic question (i.e., who\ncommitted the crime) and naturally provides the answer when the perpetrator is\nrevealed. We develop a new dataset based on CSI episodes, formalize perpetrator\nidentification as a sequence labeling problem, and develop an LSTM-based model\nwhich learns from multi-modal data. Experimental results show that an\nincremental inference strategy is key to making accurate guesses as well as\nlearning from representations fusing textual, visual, and acoustic input.","url_abs":"http://arxiv.org/abs/1710.11601v1","url_pdf":"http://arxiv.org/pdf/1710.11601v1.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":[{"paper_slug":"whodunnit-crime-drama-as-a-case-for-natural","repo_url":"https://github.com/EdinburghNLP/csi-corpus","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"natural-language-understanding","task_name":"Natural Language Understanding"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1710.11601","atlas_url":"https://app.syntology.ai/?focus=1710.11601","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}