{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:10:11Z","timestamp":1750198211146,"version":"3.41.0"},"reference-count":27,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2020,1,9]],"date-time":"2020-01-09T00:00:00Z","timestamp":1578528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Computer Research Center of Islamic Sciences"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2020,5,31]]},"abstract":"<jats:p>In this article, we present an automatic semantic role labeling system in Persian consisting of two modules: argument identification for specifying argument spans and argument classification for categorizing their semantic roles. Our modules have been trained on Persian Proposition Bank in which predicate-argument information is manually added as a layer on top of Persian Dependency Treebank with about 30,000 sentences. Therefore, our system was trained on 216,871 verbal predicates and 42,386 nonverbal ones consisting of 40,813 nouns and 1,573 adjectives with 33 semantic classes. As a supervised method, we used maximum entropy for building an argument identifier that results in human-level accuracy of 99% and support vector machine for an argument classifier with an F1 of 84. Regarding both verbal and nonverbal predicates with an expanded role set, we achieved reasonable results.<\/jats:p>","DOI":"10.1145\/3372246","type":"journal-article","created":{"date-parts":[[2020,4,4]],"date-time":"2020-04-04T03:08:03Z","timestamp":1585969683000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Semantic Role Labeling System for Persian Language"],"prefix":"10.1145","volume":"19","author":[{"given":"Azadeh","family":"Mirzaei","sequence":"first","affiliation":[{"name":"Allameh Tabataba'i University, Tehran, Iran"}]},{"given":"Fatemeh","family":"Sedghi","sequence":"additional","affiliation":[{"name":"Alzahra University, Tehran, Iran"}]},{"given":"Pegah","family":"Safari","sequence":"additional","affiliation":[{"name":"Shahid Beheshti University, Tehran, Iran"}]}],"member":"320","published-online":{"date-parts":[[2020,1,9]]},"reference":[{"volume-title":"Proceedings of the 17th International Conference on Computational Linguistics\u2014Volume 1.","author":"Baker C. 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Master\u2019s Thesis. Department of Computer Engineering","author":"Noori N.","key":"e_1_2_1_15_1"},{"key":"e_1_2_1_16_1","unstructured":"F. Oroumchian H. Amiri H. F. Raja and H. Hojjat. 2006. Creating a Feasible Corpus for Persian POS Tagging. Department of Electrical and Computer Engineering University of Tehran.  F. Oroumchian H. Amiri H. F. Raja and H. Hojjat. 2006. Creating a Feasible Corpus for Persian POS Tagging. Department of Electrical and Computer Engineering University of Tehran."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.2200\/S00239ED1V01Y200912HLT006"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1162\/0891201053630264"},{"volume-title":"Proceedings of the 5th Language and Technology Conference (LTC\u201911)","author":"Rasooli M. 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