{"id":"https://openalex.org/W2619583282","doi":"https://doi.org/10.18653/v1/w17-2609","title":"Knowledge Base Completion: Baselines Strike Back","display_name":"Knowledge Base Completion: Baselines Strike Back","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2619583282","doi":"https://doi.org/10.18653/v1/w17-2609","mag":"2619583282"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w17-2609","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2609","pdf_url":"https://www.aclweb.org/anthology/W17-2609.pdf","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 2nd Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W17-2609.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011017122","display_name":"Rudolf Kadlec","orcid":"https://orcid.org/0009-0009-6506-1721"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rudolf Kadlec","raw_affiliation_strings":["IBM Watson V Parku 4, 140 00 Prague, Czech Republic","IBM (United States), Armonk, United States"],"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, 140 00 Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050872351","display_name":"Ond\u0159ej Bajgar","orcid":"https://orcid.org/0000-0002-6208-1534"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ondrej Bajgar","raw_affiliation_strings":["IBM Watson V Parku 4, 140 00 Prague, Czech Republic","IBM (United States), Armonk, United States"],"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, 140 00 Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005624553","display_name":"Jan Kleindienst","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jan Kleindienst","raw_affiliation_strings":["IBM Watson V Parku 4, 140 00 Prague, Czech Republic","IBM (United States), Armonk, United States"],"affiliations":[{"raw_affiliation_string":"IBM Watson V Parku 4, 140 00 Prague, Czech Republic","institution_ids":[]},{"raw_affiliation_string":"IBM (United States), Armonk, United States","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011017122"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":7.2655,"has_fulltext":true,"cited_by_count":43,"citation_normalized_percentile":{"value":0.97572864,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"69","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9987000226974487,"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":0.9977999925613403,"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/baseline","display_name":"Baseline (sea)","score":0.7739092707633972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230039834976196},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.6876639723777771},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6629284024238586},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.6379855275154114},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5151978135108948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4938274323940277},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4818226397037506},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21777355670928955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10640126466751099},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08979344367980957},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08098378777503967}],"concepts":[{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.7739092707633972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230039834976196},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.6876639723777771},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6629284024238586},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.6379855275154114},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5151978135108948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4938274323940277},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4818226397037506},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21777355670928955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10640126466751099},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08979344367980957},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08098378777503967},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/w17-2609","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2609","pdf_url":"https://www.aclweb.org/anthology/W17-2609.pdf","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 2nd Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1705.10744","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.10744","pdf_url":"https://arxiv.org/pdf/1705.10744","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":"mag:2619583282","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1705.10744.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1705.10744","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1705.10744","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":"doi:10.18653/v1/w17-2609","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2609","pdf_url":"https://www.aclweb.org/anthology/W17-2609.pdf","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 2nd Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2619583282.pdf","grobid_xml":"https://content.openalex.org/works/W2619583282.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W68132019","https://openalex.org/W614875374","https://openalex.org/W1426956448","https://openalex.org/W1529533208","https://openalex.org/W1615991656","https://openalex.org/W2073587810","https://openalex.org/W2094728533","https://openalex.org/W2127426251","https://openalex.org/W2143908786","https://openalex.org/W2184957013","https://openalex.org/W2247119764","https://openalex.org/W2250184916","https://openalex.org/W2250342289","https://openalex.org/W2250911766","https://openalex.org/W2271840356","https://openalex.org/W2283196293","https://openalex.org/W2340448811","https://openalex.org/W2432356473","https://openalex.org/W2433281745","https://openalex.org/W2571811098","https://openalex.org/W2579831760","https://openalex.org/W2592634758","https://openalex.org/W2798418698","https://openalex.org/W2952558995","https://openalex.org/W2963503534","https://openalex.org/W2963688791","https://openalex.org/W2964121744","https://openalex.org/W2964152081","https://openalex.org/W3048357673"],"related_works":["https://openalex.org/W2127795553","https://openalex.org/W2094728533","https://openalex.org/W2963119656","https://openalex.org/W2145544171","https://openalex.org/W1533230146","https://openalex.org/W2283196293","https://openalex.org/W2184957013","https://openalex.org/W205829674","https://openalex.org/W2964116313","https://openalex.org/W2432356473","https://openalex.org/W2127426251","https://openalex.org/W2250184916","https://openalex.org/W1529533208","https://openalex.org/W2081580037","https://openalex.org/W2250342289","https://openalex.org/W2759136286","https://openalex.org/W2604314403","https://openalex.org/W2247119764","https://openalex.org/W2909137510","https://openalex.org/W2146502635"],"abstract_inverted_index":{"Many":[0],"papers":[1],"have":[2],"been":[3],"published":[4,46],"on":[5,28,47,68],"the":[6,12,40,48,61,69,72,100],"knowledge":[7],"base":[8],"completion":[9],"task":[10],"in":[11],"past":[13],"few":[14],"years.":[15],"Most":[16],"of":[17,42,60,75,102],"these":[18],"introduce":[19],"novel":[20],"architectures":[21],"for":[22],"relation":[23],"learning":[24],"that":[25,39,71],"are":[26,78],"evaluated":[27,105],"standard":[29],"datasets":[30],"such":[31],"as":[32,83],"FB15k":[33,49],"and":[34,106],"WN18.":[35],"This":[36,92],"paper":[37],"shows":[38],"accuracy":[41],"almost":[43],"all":[44],"models":[45,77,103],"can":[50],"be":[51],"outperformed":[52],"by":[53],"an":[54],"appropriately":[55],"tuned":[56],"baseline":[57],"-our":[58],"reimplementation":[59],"Dist-Mult":[62],"model.":[63],"Our":[64],"findings":[65],"cast":[66],"doubt":[67],"claim":[70],"performance":[73,101],"improvements":[74],"recent":[76],"due":[79],"to":[80,85,97],"architectural":[81],"changes":[82],"opposed":[84],"hyperparameter":[86],"tuning":[87],"or":[88],"different":[89],"training":[90],"objectives.":[91],"should":[93],"prompt":[94],"future":[95],"research":[96],"re-consider":[98],"how":[99],"is":[104],"reported.":[107]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2025-10-10T00:00:00"}