{"id":"https://openalex.org/W4396844354","doi":"https://doi.org/10.1145/3589335.3651263","title":"Knowledge Enabled Relation Extraction","display_name":"Knowledge Enabled Relation Extraction","publication_year":2024,"publication_date":"2024-05-12","ids":{"openalex":"https://openalex.org/W4396844354","doi":"https://doi.org/10.1145/3589335.3651263"},"language":"en","primary_location":{"id":"doi:10.1145/3589335.3651263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651263","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651263","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","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/10.1145/3589335.3651263","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005902496","display_name":"Monika Jain","orcid":"https://orcid.org/0000-0001-7697-7772"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]},{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Monika Jain","raw_affiliation_strings":["Knowledgeable Computing and Reasoning Lab, IIIT Delhi, Delhi, India"],"affiliations":[{"raw_affiliation_string":"Knowledgeable Computing and Reasoning Lab, IIIT Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005902496"],"corresponding_institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04656884,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1210","last_page":"1213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9993000030517578,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9983999729156494,"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/relation","display_name":"Relation (database)","score":0.6946557760238647},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.6363548636436462},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6336030960083008},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4366966485977173},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20437324047088623},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.06496274471282959},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.05454474687576294}],"concepts":[{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6946557760238647},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.6363548636436462},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6336030960083008},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4366966485977173},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20437324047088623},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.06496274471282959},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.05454474687576294}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589335.3651263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651263","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651263","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589335.3651263","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589335.3651263","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589335.3651263","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396844354.pdf"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2891417293","https://openalex.org/W2952179106","https://openalex.org/W2964166731","https://openalex.org/W2984452801","https://openalex.org/W3103836967","https://openalex.org/W3157022402","https://openalex.org/W3173905097","https://openalex.org/W4281935531","https://openalex.org/W4379743587","https://openalex.org/W4386566720","https://openalex.org/W4393156658"],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4285246823","https://openalex.org/W4226278302","https://openalex.org/W4385734297","https://openalex.org/W4221160509","https://openalex.org/W2547211086","https://openalex.org/W2538200646","https://openalex.org/W2888033806"],"abstract_inverted_index":{"Relation":[0],"extraction":[1,43,73],"is":[2,29,109],"the":[3,41,47,106],"task":[4,22],"of":[5,31,79],"extracting":[6],"relationships":[7],"from":[8,74],"input":[9,12],"text,":[10],"where":[11],"can":[13],"be":[14],"a":[15,91],"sentence,":[16],"document,":[17],"or":[18],"multiple":[19],"documents.":[20],"This":[21],"has":[23],"been":[24,37,103],"popular":[25,49],"for":[26,71],"decades":[27],"and":[28,59,69,83,100,105,116],"still":[30],"keen":[32],"interest.":[33],"Various":[34],"techniques":[35],"have":[36,102],"proposed":[38],"to":[39,96],"solve":[40],"relation":[42,72],"problem,":[44],"among":[45],"which":[46],"most":[48],"are":[50,113],"using":[51],"distant":[52],"supervision,":[53],"deep":[54,92],"learning-based":[55],"models,":[56,58],"reasoning-based":[57],"transformer-based":[60],"models.":[61],"We":[62,112],"propose":[63],"three":[64,77],"approaches":[65,87],"(named":[66],"ReOnto,":[67],"DocRE-CLip,":[68],"KDocRE)":[70],"text":[75],"at":[76],"levels":[78],"granularity":[80],"(sentence,":[81],"document":[82],"across":[84],"documents).":[85],"These":[86],"embed":[88],"knowledge":[89],"in":[90],"learning":[93],"based":[94],"model":[95],"improve":[97],"performance.":[98],"ReOnto":[99],"DocRE-CLip":[101],"evaluated":[104],"source":[107],"code":[108],"publicly":[110],"available.":[111],"currently":[114],"implementing":[115],"evaluating":[117],"KDocRE.":[118]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
