{"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/squinky-a-corpus-of-sentence-level-formality","title":"SQUINKY! A Corpus of Sentence-level Formality, Informativeness, and Implicature","arxiv_id":"1506.02306","date":"2015-06-07","proceeding":null,"authors":["Shibamouli Lahiri"],"abstract":"We introduce a corpus of 7,032 sentences rated by human annotators for\nformality, informativeness, and implicature on a 1-7 scale. The corpus was\nannotated using Amazon Mechanical Turk. Reliability in the obtained judgments\nwas examined by comparing mean ratings across two MTurk experiments, and\ncorrelation with pilot annotations (on sentence formality) conducted in a more\ncontrolled setting. Despite the subjectivity and inherent difficulty of the\nannotation task, correlations between mean ratings were quite encouraging,\nespecially on formality and informativeness. We further explored correlation\nbetween the three linguistic variables, genre-wise variation of ratings and\ncorrelations within genres, compatibility with automatic stylistic scoring, and\nsentential make-up of a document in terms of style. To date, our corpus is the\nlargest sentence-level annotated corpus released for formality,\ninformativeness, and implicature.","url_abs":"http://arxiv.org/abs/1506.02306v2","url_pdf":"http://arxiv.org/pdf/1506.02306v2.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":"squinky-a-corpus-of-sentence-level-formality","repo_url":"https://github.com/meyersbs/squinky","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"informativeness","task_name":"Informativeness"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1506.02306","atlas_url":"https://app.syntology.ai/?focus=1506.02306","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}