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Recent works have shown that taking advantage of relatedness between these subtasks can be beneficial. This paper proposes a unified neural framework to address these subtasks simultaneously. Apart from the sequence tagging paradigm, the proposed method tackles the multitask lexical analysis via two\u2010stage sequence span classification. Firstly, the model detects the word and named entity boundaries by multi\u2010label classification over character spans in a sentence. Then, the authors assign POS labels and entity labels for words and named entities by multi\u2010class classification, respectively. Furthermore, a Gated Task Transformation (GTT) is proposed to encourage the model to share valuable features between tasks. The performance of the proposed model was evaluated on Chinese and Thai public datasets, demonstrating state\u2010of\u2010the\u2010art results.<\/jats:p>","DOI":"10.1049\/cit2.70015","type":"journal-article","created":{"date-parts":[[2025,5,10]],"date-time":"2025-05-10T12:18:35Z","timestamp":1746879515000},"page":"1254-1267","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unified Neural Lexical Analysis Via Two\u2010Stage Span Tagging"],"prefix":"10.1049","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6411-4734","authenticated-orcid":false,"given":"Yantuan","family":"Xian","sequence":"first","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]},{"given":"Yefen","family":"Zhu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]},{"given":"Zhentao","family":"Yu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1277-6212","authenticated-orcid":false,"given":"Yuxin","family":"Huang","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]},{"given":"Junjun","family":"Guo","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]},{"given":"Yan","family":"Xiang","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming University of Science and Technology  Kunming China"},{"name":"Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology  Kunming China"}]}],"member":"265","published-online":{"date-parts":[[2025,5,10]]},"reference":[{"key":"e_1_2_11_2_1","first-page":"29","article-title":"Chinese Word Segmentation as Character Tagging","author":"Xue N.","year":"2003","journal-title":"International Journal of Computational Linguistics & Chinese Language Processing"},{"key":"e_1_2_11_3_1","article-title":"Part\u2010of\u2010Speech Tagging With Bidirectional Long Short\u2010Term Memory Recurrent Neural Network","author":"Wang P.","year":"2015","journal-title":"CoRR"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2020.2981314"},{"key":"e_1_2_11_5_1","unstructured":"Y.Shao C.Hardmeier J.Tiedemann J.Nivre.Character\u2010based Joint Segmentation and POS Tagging for Chinese Using Bidirectional RNN\u2010CRF(2017) 173\u2013183."},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/taslp.2017.2788181"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/taslp.2018.2830117"},{"key":"e_1_2_11_8_1","unstructured":"SunY. 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