{"id":"https://openalex.org/W4399415211","doi":"https://doi.org/10.1109/tetci.2024.3406440","title":"A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction","display_name":"A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction","publication_year":2024,"publication_date":"2024-06-06","ids":{"openalex":"https://openalex.org/W4399415211","doi":"https://doi.org/10.1109/tetci.2024.3406440"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2024.3406440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3406440","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113012130","display_name":"Jian Cheng","orcid":"https://orcid.org/0000-0002-9805-8870"},"institutions":[{"id":"https://openalex.org/I4210133666","display_name":"Tiandi Science & Technology (China)","ror":"https://ror.org/03ssr6t63","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210133666"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Cheng","raw_affiliation_strings":["Research Institute of Mine Artificial Intelligence in Chinese Institute of Coal Science, State Key Laboratory of Intelligent Coal Mining and Strata Control, and Tiandi Science and Technology Company Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Mine Artificial Intelligence in Chinese Institute of Coal Science, State Key Laboratory of Intelligent Coal Mining and Strata Control, and Tiandi Science and Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210133666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108950939","display_name":"Tian Zhang","orcid":"https://orcid.org/0000-0002-0538-1071"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Zhang","raw_affiliation_strings":["College of Software, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Software, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114859996","display_name":"Shuang Zhang","orcid":"https://orcid.org/0009-0004-3958-7213"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Zhang","raw_affiliation_strings":["College of Software, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Software, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057609241","display_name":"Huimin Ren","orcid":"https://orcid.org/0000-0002-8462-9417"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Ren","raw_affiliation_strings":["College of Software, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Software, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053841201","display_name":"Guo Yu","orcid":"https://orcid.org/0000-0003-2427-8202"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo Yu","raw_affiliation_strings":["Institute of Intelligent Manufacturing, Nanjing Tech University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Manufacturing, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612913","display_name":"Xiliang Zhang","orcid":"https://orcid.org/0000-0002-5339-8329"},"institutions":[{"id":"https://openalex.org/I135905480","display_name":"Shanghai Polytechnic University","ror":"https://ror.org/02as5yg64","country_code":"CN","type":"education","lineage":["https://openalex.org/I135905480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiliang Zhang","raw_affiliation_strings":["School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai, China","institution_ids":["https://openalex.org/I135905480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010245958","display_name":"Shangce Gao","orcid":"https://orcid.org/0000-0001-5042-3261"},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shangce Gao","raw_affiliation_strings":["Faculty of Engineering, University of Toyama, Toyama-Shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Toyama, Toyama-Shi, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068061222","display_name":"Lianbo Ma","orcid":"https://orcid.org/0000-0002-9969-211X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianbo Ma","raw_affiliation_strings":["College of Software, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Software, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5113012130"],"corresponding_institution_ids":["https://openalex.org/I4210133666"],"apc_list":null,"apc_paid":null,"fwci":3.1276,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.9242002,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"9","issue":"2","first_page":"1130","last_page":"1142"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9225000143051147,"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":0.9225000143051147,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.8391376733779907},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6801514625549316},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5882101655006409},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5647413730621338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48874330520629883},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4302988350391388},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.41982564330101013},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22394704818725586},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13337400555610657},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.10945537686347961},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.09453985095024109},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.05497288703918457},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.054256170988082886}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.8391376733779907},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6801514625549316},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5882101655006409},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5647413730621338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48874330520629883},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4302988350391388},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.41982564330101013},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22394704818725586},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13337400555610657},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.10945537686347961},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.09453985095024109},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.05497288703918457},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.054256170988082886},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2024.3406440","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3406440","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3578109697","display_name":null,"funder_award_id":"62103150","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G422653279","display_name":null,"funder_award_id":"62333010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6776388358","display_name":null,"funder_award_id":"2024A1515012016","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1546862366","https://openalex.org/W1604644367","https://openalex.org/W2064675550","https://openalex.org/W2134033474","https://openalex.org/W2250539671","https://openalex.org/W2251091211","https://openalex.org/W2517194566","https://openalex.org/W2519969774","https://openalex.org/W2539469848","https://openalex.org/W2587809655","https://openalex.org/W2739874095","https://openalex.org/W2741956709","https://openalex.org/W2798734500","https://openalex.org/W2799125718","https://openalex.org/W2808142148","https://openalex.org/W2891935547","https://openalex.org/W2896457183","https://openalex.org/W2905462022","https://openalex.org/W2949212908","https://openalex.org/W2951231735","https://openalex.org/W2951274974","https://openalex.org/W2952278429","https://openalex.org/W2962913831","https://openalex.org/W2963602416","https://openalex.org/W2964167098","https://openalex.org/W2964349647","https://openalex.org/W2965831155","https://openalex.org/W2966874979","https://openalex.org/W2970183140","https://openalex.org/W2995837271","https://openalex.org/W2996825178","https://openalex.org/W2996913633","https://openalex.org/W2997876626","https://openalex.org/W3034617555","https://openalex.org/W3034902017","https://openalex.org/W3090145439","https://openalex.org/W3095696617","https://openalex.org/W3105063288","https://openalex.org/W3116427155","https://openalex.org/W3160836059","https://openalex.org/W4220958359","https://openalex.org/W4285173594","https://openalex.org/W4312729467","https://openalex.org/W4363676972","https://openalex.org/W4379652941","https://openalex.org/W4385570269","https://openalex.org/W4385571037","https://openalex.org/W4386702673","https://openalex.org/W6691723933","https://openalex.org/W6732551439"],"related_works":["https://openalex.org/W2153719181","https://openalex.org/W1971748923","https://openalex.org/W1566155057","https://openalex.org/W2060986072","https://openalex.org/W2052574922","https://openalex.org/W64588465","https://openalex.org/W3120641340","https://openalex.org/W2117825986","https://openalex.org/W3134067061","https://openalex.org/W2079855347"],"abstract_inverted_index":{"In":[0,53,147],"knowledge":[1],"graph":[2],"construction,":[3],"a":[4,18,70,75,86,91,102,143,162],"challenging":[5],"issue":[6],"is":[7,81,127],"how":[8],"to":[9,30,50,63,114,171],"extract":[10,64],"complex":[11],"(e.g.,":[12],"overlapping)":[13],"entities":[14,141],"and":[15,47,74,83,90,139,167,182,188],"relationships":[16],"from":[17,101],"small":[19],"amount":[20],"of":[21,118,184],"unstructured":[22],"historical":[23],"data.":[24],"The":[25,95,176],"traditional":[26],"pipeline":[27],"methods":[28],"are":[29],"divide":[31],"the":[32,40,44,105,115,119,131,136,150,173,180],"extraction":[33],"into":[34],"two":[35,45,168],"separate":[36],"subtasks,":[37],"which":[38,68,126],"misses":[39],"potential":[41],"interactio":[42],"between":[43],"subtasks":[46],"may":[48],"lead":[49],"error":[51],"propagation.":[52],"this":[54,112,148],"work,":[55],"we":[56],"propose":[57],"an":[58],"effective":[59],"cascade":[60],"dual-decoder":[61],"method":[62,187],"overlapping":[65,151],"relational":[66],"triples,":[67],"includes":[69,85],"text-specific":[71,87,96],"relation":[72,88,97],"decoder":[73,89,98,134],"relation-corresponded":[76,92,132],"entity":[77,93,133],"decoder.":[78,94],"Our":[79],"approach":[80],"straightforward":[82],"it":[84,110],"detects":[99,135],"relations":[100],"sentence":[103],"at":[104],"text":[106],"level.":[107],"That":[108],"is,":[109],"does":[111],"according":[113],"semantic":[116],"information":[117],"whole":[120],"sentence.":[121],"For":[122],"each":[123],"extracted":[124],"relation,":[125],"with":[128],"trainable":[129],"embedding,":[130],"corresponding":[137],"head":[138],"tail":[140],"using":[142],"span-based":[144],"tagging":[145],"scheme.":[146],"way,":[149],"triple":[152],"problem":[153],"can":[154],"be":[155],"tackled":[156],"naturally.":[157],"We":[158],"conducted":[159],"experiments":[160],"on":[161],"real-world":[163],"open-pit":[164],"mine":[165],"dataset":[166],"public":[169],"datasets":[170],"verify":[172],"method's":[174],"generalizability.":[175],"experimental":[177],"results":[178],"demonstrate":[179],"effectiveness":[181],"competitiveness":[183],"our":[185],"proposed":[186],"achieve":[189],"better":[190],"F1":[191],"scores":[192],"under":[193],"strict":[194],"evaluation":[195],"metrics.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
