{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T20:59:20Z","timestamp":1778965160238,"version":"3.51.4"},"reference-count":25,"publisher":"China Science Publishing & Media Ltd.","issue":"3","license":[{"start":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T00:00:00Z","timestamp":1617062400000},"content-version":"vor","delay-in-days":88,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,9,8]]},"abstract":"<jats:p>The China Conference on Knowledge Graph and Semantic Computing (CCKS) 2020 Evaluation Task 3 presented clinical named entity recognition and event extraction for the Chinese electronic medical records. Two annotated data sets and some other additional resources for these two subtasks were provided for participators. This evaluation competition attracted 354 teams and 46 of them successfully submitted the valid results. The pre-trained language models are widely applied in this evaluation task. Data argumentation and external resources are also helpful.<\/jats:p>","DOI":"10.1162\/dint_a_00093","type":"journal-article","created":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T19:40:17Z","timestamp":1617133217000},"page":"376-388","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":20,"title":["Overview of CCKS 2020 Task 3: Named Entity Recognition and Event\n                    Extraction in Chinese Electronic Medical Records"],"prefix":"10.3724","volume":"3","author":[{"given":"Xia","family":"Li","sequence":"first","affiliation":[{"name":"The 305th Hospital of the Chinese People's Liberation Army, Wenjin Street, Xicheng District, Beijing 100017, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghua","family":"Wen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, 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