{"id":"https://openalex.org/W4368618872","doi":"https://doi.org/10.48550/arxiv.2305.01555","title":"How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?","display_name":"How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?","publication_year":2023,"publication_date":"2023-05-02","ids":{"openalex":"https://openalex.org/W4368618872","doi":"https://doi.org/10.48550/arxiv.2305.01555"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2305.01555","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.01555","pdf_url":"https://arxiv.org/pdf/2305.01555","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.01555","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100319817","display_name":"Xin Xu","orcid":"https://orcid.org/0009-0002-2319-1682"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xu, Xin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102421790","display_name":"Yuqi Zhu","orcid":"https://orcid.org/0009-0007-1299-1744"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yuqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354377","display_name":"Xiaohan Wang","orcid":"https://orcid.org/0000-0001-6206-7911"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaohan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066906745","display_name":"Ningyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ningyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100319817"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/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/T13629","display_name":"Text Readability and Simplification","score":0.9509999752044678,"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":0.8482139706611633},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.7620173692703247},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.641796886920929},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5428102612495422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.530129611492157},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5003411769866943},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4838653802871704},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4267335534095764},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.4257206320762634},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31788063049316406},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2474452257156372}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8482139706611633},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7620173692703247},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.641796886920929},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5428102612495422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.530129611492157},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5003411769866943},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4838653802871704},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4267335534095764},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.4257206320762634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31788063049316406},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2474452257156372},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2305.01555","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.01555","pdf_url":"https://arxiv.org/pdf/2305.01555","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2305.01555","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2305.01555","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.01555","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.01555","pdf_url":"https://arxiv.org/pdf/2305.01555","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2555641306","display_name":null,"funder_award_id":"2021J1","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G3639257505","display_name":null,"funder_award_id":"2021J190","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G4550267742","display_name":null,"funder_award_id":"62206246","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7528831822","display_name":null,"funder_award_id":"LGG22F030011","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332587","display_name":"Natural Science Foundation of Ningbo","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4368618872.pdf","grobid_xml":"https://content.openalex.org/works/W4368618872.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4285246823","https://openalex.org/W2045408812","https://openalex.org/W4226278302","https://openalex.org/W4385734297","https://openalex.org/W2547211086","https://openalex.org/W4221160509","https://openalex.org/W2888033806"],"abstract_inverted_index":{"Scaling":[0],"language":[1,17,74,105],"models":[2,106],"have":[3],"revolutionized":[4],"widespread":[5],"NLP":[6],"tasks,":[7],"yet":[8],"little":[9],"comprehensively":[10],"explored":[11],"few-shot":[12,32,42,84,108],"relation":[13,33,89,109],"extraction":[14,34,90],"with":[15,63,71],"large":[16,73,104],"models.":[18],"In":[19],"this":[20],"paper,":[21],"we":[22,44],"investigate":[23],"principal":[24],"methodologies,":[25],"in-context":[26,56],"learning":[27,57,66],"and":[28,49,68],"data":[29,51,69],"generation,":[30],"for":[31,100],"via":[35],"GPT-3.5":[36],"through":[37],"exhaustive":[38],"experiments.":[39],"To":[40],"enhance":[41],"performance,":[43],"further":[45],"propose":[46],"task-related":[47],"instructions":[48],"schema-constrained":[50],"generation.":[52],"We":[53,92],"observe":[54],"that":[55],"can":[58,76,96],"achieve":[59],"performance":[60],"on":[61,86],"par":[62],"previous":[64,78],"prompt":[65],"approaches,":[67],"generation":[70],"the":[72,101],"model":[75],"boost":[77],"solutions":[79],"to":[80],"obtain":[81],"new":[82],"state-of-the-art":[83],"results":[85],"four":[87],"widely-studied":[88],"datasets.":[91],"hope":[93],"our":[94],"work":[95],"inspire":[97],"future":[98],"research":[99],"capabilities":[102],"of":[103],"in":[107,114],"extraction.":[110],"Code":[111],"is":[112],"available":[113],"https://github.com/zjunlp/DeepKE/tree/main/example/llm.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}