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However, existing methods often assume the independence of utterance and model them in isolation. In this paper, we propose a Dependency paRsing\u2010Enhanced converSational queStion AnswerinG systEm, DRESSAGE, which can effectively model long\u2010range semantic dependencies in the conversation history. This is a multitask neural semantic parsing model. The model can perform explicit dependency parsing for several history questions and the current question and enhance the entity recognition module and the question encoding module with the parsing tree. The performance of the DRESSAGE model is tested on the widely used CSQA dataset and gets SOTA in the overall effect, which proves the effectiveness of this model.<\/jats:p>","DOI":"10.1155\/int\/1977785","type":"journal-article","created":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T06:03:39Z","timestamp":1766383419000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dependency Parsing\u2010Enhanced Conversational Knowledge\u2010Based Question Answering System"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6229-8565","authenticated-orcid":false,"given":"Jinhao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9351-6708","authenticated-orcid":false,"given":"Xu","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0762-687X","authenticated-orcid":false,"given":"Ming","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinchuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,12,21]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-024-05282-8"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127141"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i17.29938"},{"key":"e_1_2_10_4_2","doi-asserted-by":"crossref","unstructured":"DingW. 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