{"id":"https://openalex.org/W4375869293","doi":"https://doi.org/10.1109/icassp49357.2023.10095912","title":"TABLEIE: Capturing the Interactions Among Sub-Tasks in Information Extraction via Double Tables","display_name":"TABLEIE: Capturing the Interactions Among Sub-Tasks in Information Extraction via Double Tables","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4375869293","doi":"https://doi.org/10.1109/icassp49357.2023.10095912"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095912","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10095912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5053055634","display_name":"Jiaxing Lin","orcid":"https://orcid.org/0000-0003-3193-5522"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxing Lin","raw_affiliation_strings":["Peking University,Key Laboratory of Computational Linguistics,MOE,China","Key Laboratory of Computational Linguistics, Peking University, MOE, China","School of Software and Microelectronics, Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of Computational Linguistics,MOE,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Laboratory of Computational Linguistics, Peking University, MOE, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Software and Microelectronics, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023594937","display_name":"Runxin Xu","orcid":"https://orcid.org/0000-0002-3876-2284"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runxin Xu","raw_affiliation_strings":["Peking University,Key Laboratory of Computational Linguistics,MOE,China","Key Laboratory of Computational Linguistics, Peking University, MOE, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of Computational Linguistics,MOE,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Laboratory of Computational Linguistics, Peking University, MOE, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021459300","display_name":"Baobao Chang","orcid":"https://orcid.org/0000-0003-2824-6750"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baobao Chang","raw_affiliation_strings":["Peking University,Key Laboratory of Computational Linguistics,MOE,China","Key Laboratory of Computational Linguistics, Peking University, MOE, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University,Key Laboratory of Computational Linguistics,MOE,China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Laboratory of Computational Linguistics, Peking University, MOE, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.2178,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39389225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T11719","display_name":"Data Quality and Management","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.8273955583572388},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.668650209903717},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6576700210571289},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6269178986549377},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5973890423774719},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4847356975078583},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4795943796634674},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4532301723957062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43759065866470337},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41942501068115234},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4151090681552887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4097290635108948},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3913782238960266},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16528984904289246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8273955583572388},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.668650209903717},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6576700210571289},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6269178986549377},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5973890423774719},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4847356975078583},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4795943796634674},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4532301723957062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43759065866470337},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41942501068115234},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4151090681552887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4097290635108948},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3913782238960266},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16528984904289246},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095912","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10095912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2008830554","https://openalex.org/W2132516856","https://openalex.org/W2134033474","https://openalex.org/W2250575108","https://openalex.org/W2250999640","https://openalex.org/W2296283641","https://openalex.org/W2896457183","https://openalex.org/W2963718112","https://openalex.org/W2965373594","https://openalex.org/W2970501962","https://openalex.org/W2984582583","https://openalex.org/W3035169087","https://openalex.org/W3035229828","https://openalex.org/W3167337824","https://openalex.org/W3168204696","https://openalex.org/W6679676213","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2369351710","https://openalex.org/W2594363579","https://openalex.org/W2169232658"],"abstract_inverted_index":{"Information":[0],"Extraction":[1,11],"mainly":[2],"consists":[3],"of":[4,31,58,123],"three":[5],"sub-tasks,":[6],"Named":[7],"Entity":[8],"Recognition,":[9],"Relation":[10],"and":[12,33,99,110],"Event":[13],"Extraction.":[14],"Although":[15],"these":[16],"sub-tasks":[17,85],"are":[18,44],"highly":[19],"correlated":[20],"with":[21,180],"each":[22],"other,":[23],"most":[24],"previous":[25,151,177],"works":[26],"simply":[27],"focus":[28],"on":[29,104,156],"part":[30],"them":[32],"ignore":[34],"the":[35,49,56,67,81,90,133,136,150,157,166,176,184],"interactions":[36,50,82],"among":[37,51,83],"different":[38,52],"sub-tasks.":[39,54],"Recently,":[40],"some":[41],"graph-based":[42,178],"models":[43],"proposed":[45],"to":[46,79,127,154],"cover":[47],"all":[48],"IE":[53,84],"However,":[55],"use":[57,122],"Graph":[59],"Neural":[60],"Network":[61],"brings":[62],"heavy":[63],"computation":[64],"burden,":[65],"damaging":[66],"model":[68,91],"efficiency.":[69,92],"In":[70],"this":[71],"paper,":[72],"we":[73,106,139],"propose":[74,107],"a":[75,114],"double-table":[76],"framework,":[77],"TableIE,":[78],"capture":[80],"as":[86,88],"well":[87],"improve":[89],"Specifically,":[93],"TableIE":[94,148,162],"has":[95],"an":[96,100,124],"entity-relation":[97],"table":[98,116,134],"event":[101],"table,":[102],"based":[103],"which":[105,138],"both":[108],"within-table":[109],"cross-table":[111],"interaction":[112],"through":[113],"novel":[115],"integration":[117],"technique.":[118],"Such":[119],"technique":[120],"makes":[121],"information-aware":[125],"mask":[126],"extract":[128],"more":[129,173],"essential":[130],"information":[131],"in":[132,183],"during":[135],"integration,":[137],"call":[140],"discriminative":[141],"interaction.":[142],"Our":[143,187],"extensive":[144],"experiments":[145],"demonstrate":[146],"that":[147],"outperforms":[149],"state-of-the-art":[152],"up":[153],"1.4":[155],"ACE05":[158],"dataset.":[159],"Besides,":[160],"since":[161],"does":[163],"not":[164],"involve":[165],"time-consuming":[167],"graph":[168],"operation,":[169],"it":[170],"is":[171,189],"also":[172],"efficient":[174],"than":[175],"models,":[179],"13x":[181],"speed-up":[182],"inference":[185],"stage.":[186],"code":[188],"available":[190],"at":[191],"https://github.com/PKUnlp-icler/TableIE":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
