{"id":"https://openalex.org/W4401815768","doi":"https://doi.org/10.1145/3689629","title":"Knowledge-injected Prompt Learning for Chinese Biomedical Entity Normalization","display_name":"Knowledge-injected Prompt Learning for Chinese Biomedical Entity Normalization","publication_year":2024,"publication_date":"2024-08-23","ids":{"openalex":"https://openalex.org/W4401815768","doi":"https://doi.org/10.1145/3689629"},"language":"en","primary_location":{"id":"doi:10.1145/3689629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3689629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3689629","source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3689629","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032473436","display_name":"Songhua Yang","orcid":"https://orcid.org/0000-0002-7301-4425"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songhua Yang","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7301-4425","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057493077","display_name":"Chenghao Zhang","orcid":"https://orcid.org/0000-0002-3555-1553"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghao Zhang","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3555-1553","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109768010","display_name":"Chenyuan He","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyuan He","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-9169-9553","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049783368","display_name":"Hongfei Xu","orcid":"https://orcid.org/0000-0001-8397-1459"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongfei Xu","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8397-1459","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062969664","display_name":"Hongying Zan","orcid":"https://orcid.org/0000-0002-8874-1262"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongying Zan","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8874-1262","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064013704","display_name":"Yuxiang Jia","orcid":"https://orcid.org/0000-0003-0481-0740"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Jia","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0481-0740","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.8335,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77156272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"23","issue":"10","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7248181104660034},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49314993619918823},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4273379147052765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40340733528137207},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.06716039776802063}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7248181104660034},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49314993619918823},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4273379147052765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40340733528137207},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.06716039776802063},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3689629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3689629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3689629","source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3689629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3689629","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3689629","source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.75}],"awards":[{"id":"https://openalex.org/G3732306342","display_name":null,"funder_award_id":"232300421386","funder_id":"https://openalex.org/F4320323845","funder_display_name":"Natural Science Foundation of Henan Province"},{"id":"https://openalex.org/G8081367761","display_name":null,"funder_award_id":"62306284","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8940753486","display_name":null,"funder_award_id":"2023M743189","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320323845","display_name":"Natural Science Foundation of Henan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401815768.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1034019924","https://openalex.org/W2116040937","https://openalex.org/W2123439964","https://openalex.org/W2142016317","https://openalex.org/W2159583324","https://openalex.org/W2206373005","https://openalex.org/W2259159222","https://openalex.org/W2325227998","https://openalex.org/W2593581739","https://openalex.org/W2599674900","https://openalex.org/W2602753196","https://openalex.org/W2763990719","https://openalex.org/W2892737606","https://openalex.org/W2911489562","https://openalex.org/W2925863688","https://openalex.org/W2948306594","https://openalex.org/W2967690619","https://openalex.org/W2983952025","https://openalex.org/W3014809049","https://openalex.org/W3081505754","https://openalex.org/W3101372913","https://openalex.org/W3143835353","https://openalex.org/W3162532547","https://openalex.org/W3174044761","https://openalex.org/W3174770825","https://openalex.org/W3185341429","https://openalex.org/W3216703728","https://openalex.org/W4205713900","https://openalex.org/W4205807230","https://openalex.org/W4226166716","https://openalex.org/W4239510810","https://openalex.org/W4283791421","https://openalex.org/W4309811444","https://openalex.org/W4312447004","https://openalex.org/W4323362555","https://openalex.org/W4377086303","https://openalex.org/W6745479485","https://openalex.org/W6766960179"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W4321441197","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0],"Biomedical":[1],"Entity":[2],"Normalization":[3],"(BEN)":[4],"task":[5],"aims":[6],"to":[7,13,135],"align":[8],"raw,":[9],"unstructured":[10],"medical":[11,24,60,69,119,140],"entities":[12,120],"standard":[14,149],"entities,":[15,141],"thus":[16,142],"promoting":[17],"data":[18],"coherence":[19],"and":[20,62,108,121,162,181],"facilitating":[21],"better":[22,145],"downstream":[23],"applications.":[25],"Recently,":[26],"prompt":[27],"learning":[28],"methods":[29],"have":[30],"shown":[31],"promising":[32],"results":[33],"in":[34,45,54,118,159,179,185,191],"the":[35,47,55,63,67,93,114,128,132,148,192],"natural":[36],"language":[37],"processing":[38],"field.":[39],"However,":[40],"existing":[41,168],"research":[42],"falls":[43],"short":[44],"tackling":[46],"more":[48],"complex":[49],"Chinese":[50],"BEN":[51,193],"task,":[52],"especially":[53],"few-shot":[56,161,180],"scenario":[57],"with":[58,147,170],"limited":[59],"data,":[61],"vast":[64],"potential":[65],"of":[66,96,175],"external":[68],"knowledge":[70,102,104,106,115,130],"base":[71],"has":[72],"not":[73],"yet":[74],"been":[75],"fully":[76],"exploited.":[77],"To":[78],"address":[79],"these":[80],"challenges,":[81],"this":[82],"article":[83],"proposes":[84],"a":[85,144,156],"novel":[86],"Knowledge-injected":[87],"Prompt":[88],"Learning":[89],"(PL-Knowledge)":[90],"method.":[91],"Specifically,":[92],"approach":[94],"consists":[95],"five":[97],"stages:":[98],"candidate":[99],"entity":[100],"matching,":[101],"extraction,":[103],"encoding,":[105],"injection,":[107],"prediction":[109],"output.":[110],"By":[111],"effectively":[112],"encoding":[113],"items":[116],"contained":[117],"incorporating":[122],"them":[123],"into":[124],"tailor-made":[125],"knowledge-injected":[126],"templates,":[127],"additional":[129],"enhances":[131],"model\u2019s":[133],"ability":[134],"capture":[136],"latent":[137],"relationships":[138],"between":[139],"achieving":[143],"match":[146],"entities.":[150],"Comprehensive":[151],"experiments":[152],"are":[153],"conducted":[154],"on":[155],"benchmark":[157],"dataset":[158],"both":[160],"full-scale":[163],"settings.":[164],"This":[165],"method":[166],"outperforms":[167],"baselines,":[169],"an":[171],"average":[172],"accuracy":[173],"improvement":[174],"12.96":[176],"percentage":[177,183],"points":[178,184],"0.94":[182],"full-data":[186],"cases,":[187],"showcasing":[188],"its":[189],"excellence":[190],"task.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}