{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:50:22Z","timestamp":1747216222974,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643684246"},{"type":"electronic","value":"9781643684253"}],"license":[{"start":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T00:00:00Z","timestamp":1694390400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,11]]},"abstract":"<jats:p>The aim of this study is to identify idiomatic expressions in English using the measure perplexity. The assumption is that idiomatic expressions cause higher perplexity than literal expressions given a reference text. Perplexity in our study is calculated based on n-grams of (i) PoS tags, (ii) tokens, and (iii) thematic roles within the boundaries of a sentence. In the setting of our study, we observed that no perplexity in the contexts of (i), (ii) and (iii) manages to distinguish idiomatic expressions from literals. We postulate that larger, extra-sentential contexts should be used for the determination of perplexity. In addition, the number of thematic roles in (iii) should be reduced to a smaller number of basic roles in order to avaiod an uniform distribution of n-grams.<\/jats:p>","DOI":"10.3233\/ssw230006","type":"book-chapter","created":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T08:18:29Z","timestamp":1695025109000},"source":"Crossref","is-referenced-by-count":0,"title":["Perplexed by Idioms?"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0577-7831","authenticated-orcid":false,"given":"J. Nathanael","family":"Philipp","sequence":"first","affiliation":[{"name":"Serbski institut"},{"name":"Leipzig University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7460-4139","authenticated-orcid":false,"given":"Max","family":"K\u00f6lbl","sequence":"additional","affiliation":[{"name":"Osaka University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0879-0878","authenticated-orcid":false,"given":"Erik","family":"Daas","sequence":"additional","affiliation":[{"name":"Leipzig University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuki","family":"Kyogoku","sequence":"additional","affiliation":[{"name":"Leipzig University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7460-4139","authenticated-orcid":false,"given":"Michael","family":"Richter","sequence":"additional","affiliation":[{"name":"Leipzig University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies on the Semantic Web","Knowledge Graphs: Semantics, Machine Learning, and Languages"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SSW230006","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T08:18:30Z","timestamp":1695025110000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SSW230006"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,11]]},"ISBN":["9781643684246","9781643684253"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/ssw230006","relation":{},"ISSN":["1868-1158","2215-0870"],"issn-type":[{"type":"print","value":"1868-1158"},{"type":"electronic","value":"2215-0870"}],"subject":[],"published":{"date-parts":[[2023,9,11]]}}}