{"id":"https://openalex.org/W4401856712","doi":"https://doi.org/10.1145/3637528.3671857","title":"Ontology Enrichment for Effective Fine-grained Entity Typing","display_name":"Ontology Enrichment for Effective Fine-grained Entity Typing","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401856712","doi":"https://doi.org/10.1145/3637528.3671857"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671857","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671857","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671857","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002970439","display_name":"Siru Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Siru Ouyang","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046688345","display_name":"Jiaxin Huang","orcid":"https://orcid.org/0000-0001-8095-3343"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxin Huang","raw_affiliation_strings":["Washington University in Saint Louis, St. Louis, MO, USA"],"affiliations":[{"raw_affiliation_string":"Washington University in Saint Louis, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033031380","display_name":"Pranav Pillai","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pranav Pillai","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062324293","display_name":"Yunyi Zhang","orcid":"https://orcid.org/0000-0001-9790-4855"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunyi Zhang","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003837744","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0003-0540-6758"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019539533","display_name":"Jiawei Han","orcid":"https://orcid.org/0000-0002-3629-2696"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Han","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5002970439"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":1.3901,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84281286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2318","last_page":"2327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994999766349792,"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":0.9818999767303467,"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/computer-science","display_name":"Computer science","score":0.8537462949752808},{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.7664294242858887},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6541489958763123},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.58587646484375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5513522028923035},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5066371560096741},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4849153161048889},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.44516441226005554},{"id":"https://openalex.org/keywords/open-biomedical-ontologies","display_name":"Open Biomedical Ontologies","score":0.44029441475868225},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.42891770601272583},{"id":"https://openalex.org/keywords/ontology-alignment","display_name":"Ontology alignment","score":0.3004378080368042},{"id":"https://openalex.org/keywords/upper-ontology","display_name":"Upper ontology","score":0.2935599088668823},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.15648993849754333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8537462949752808},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.7664294242858887},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6541489958763123},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.58587646484375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5513522028923035},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5066371560096741},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4849153161048889},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.44516441226005554},{"id":"https://openalex.org/C137982476","wikidata":"https://www.wikidata.org/wiki/Q7072326","display_name":"Open Biomedical Ontologies","level":5,"score":0.44029441475868225},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.42891770601272583},{"id":"https://openalex.org/C98893333","wikidata":"https://www.wikidata.org/wiki/Q4339878","display_name":"Ontology alignment","level":4,"score":0.3004378080368042},{"id":"https://openalex.org/C78726541","wikidata":"https://www.wikidata.org/wiki/Q3882785","display_name":"Upper ontology","level":3,"score":0.2935599088668823},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.15648993849754333},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671857","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671857","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3637528.3671857","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671857","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671857","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401856712.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1840435438","https://openalex.org/W2101114896","https://openalex.org/W2138605095","https://openalex.org/W2283140239","https://openalex.org/W2564425030","https://openalex.org/W2788024509","https://openalex.org/W2798442412","https://openalex.org/W2798943914","https://openalex.org/W2888846440","https://openalex.org/W2946531303","https://openalex.org/W2951994466","https://openalex.org/W2962713724","https://openalex.org/W2962756504","https://openalex.org/W2970076461","https://openalex.org/W2997110185","https://openalex.org/W3035586841","https://openalex.org/W3153385943","https://openalex.org/W3176589722","https://openalex.org/W3194309076","https://openalex.org/W4206745025","https://openalex.org/W4225716497","https://openalex.org/W4318186628","https://openalex.org/W4386811773","https://openalex.org/W4389523757","https://openalex.org/W4389523957"],"related_works":["https://openalex.org/W274732444","https://openalex.org/W2127299687","https://openalex.org/W2386232412","https://openalex.org/W2793451634","https://openalex.org/W149627178","https://openalex.org/W22148886","https://openalex.org/W4206428734","https://openalex.org/W152870918","https://openalex.org/W1794266373","https://openalex.org/W2357882026"],"abstract_inverted_index":{"Fine-grained":[0],"entity":[1,10,17,181],"typing":[2,153,182],"(FET)":[3],"is":[4,33,64],"the":[5,38,55,127,157],"task":[6],"of":[7,41,57,109,133],"identifying":[8],"specific":[9],"types":[11,145],"at":[12],"a":[13,151,191],"fine-grained":[14,180],"level":[15],"for":[16,26,137],"mentions":[18],"based":[19],"on":[20],"their":[21,107],"contextual":[22],"information.":[23],"Conventional":[24],"methods":[25,189],"FET":[27,59,104],"require":[28],"extensive":[29],"human":[30,184],"annotation,":[31,185],"which":[32],"time-consuming":[34],"and":[35,75,95,148,168,194,205],"costly":[36],"given":[37],"massive":[39],"scale":[40],"data.":[42],"Recent":[43],"studies":[44],"have":[45],"been":[46],"developing":[47],"weakly":[48],"supervised":[49,196],"or":[50],"zero-shot":[51,58,96,103,188],"approaches.":[52],"We":[53,208],"study":[54],"setting":[56],"where":[60,120],"only":[61],"an":[62,162],"ontology":[63,69,128],"provided.":[65],"However,":[66],"most":[67],"existing":[68,187],"structures":[70],"lack":[71,108],"rich":[72],"supporting":[73],"information":[74,136,142,159],"even":[76],"contain":[77],"ambiguous":[78],"relations,":[79],"making":[80],"them":[81],"ineffective":[82],"in":[83,92,102,126],"guiding":[84],"FET.":[85],"Recently":[86],"developed":[87],"language":[88],"models,":[89],"though":[90],"promising":[91],"various":[93],"few-shot":[94],"NLP":[97],"tasks,":[98],"may":[99],"face":[100],"challenges":[101],"due":[105],"to":[106,143,203],"interaction":[110],"with":[111,130,146,165],"task-specific":[112],"ontology.":[113],"In":[114],"this":[115,212],"study,":[116],"we":[117,121],"propose":[118],"\u00f8urs,":[119],"(1)":[122],"enrich":[123],"each":[124],"node":[125],"structure":[129],"two":[131],"categories":[132],"extra":[134],"information:instance":[135],"training":[138,161,171],"sample":[139],"augmentation":[140],"andtopic":[141],"relate":[144],"contexts,":[147],"(2)":[149],"develop":[150],"coarse-to-fine":[152],"algorithm":[154],"that":[155,176],"exploits":[156],"enriched":[158],"by":[160,190],"entailment":[163],"model":[164],"contrasting":[166],"topics":[167],"instance-based":[169],"augmented":[170],"samples.":[172],"Our":[173],"experiments":[174],"show":[175],"\u00f8urs":[177,198],"achieves":[178],"high-quality":[179],"without":[183],"outperforming":[186],"large":[192],"margin":[193],"rivaling":[195],"methods.":[197],"also":[199],"enjoys":[200],"strong":[201],"transferability":[202],"unseen":[204],"finer-grained":[206],"types.":[207],"will":[209],"open":[210],"source":[211],"work":[213],"upon":[214],"acceptance.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}