{"id":"https://openalex.org/W3004074269","doi":"https://doi.org/10.1162/tacl_a_00332","title":"Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs","display_name":"Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs","publication_year":2020,"publication_date":"2020-09-16","ids":{"openalex":"https://openalex.org/W3004074269","doi":"https://doi.org/10.1162/tacl_a_00332","mag":"3004074269"},"language":"en","primary_location":{"id":"doi:10.1162/tacl_a_00332","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00332","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00332/1923190/tacl_a_00332.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00332/1923190/tacl_a_00332.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063685873","display_name":"Leonardo F. R. Ribeiro","orcid":"https://orcid.org/0000-0003-2639-942X"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Leonardo F. R. Ribeiro","raw_affiliation_strings":["Research Training Group AIPHES and UKP Lab, Technische Universit\u00e4t Darmstadt","Technische Universit\u00e4t Darmstadt,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Training Group AIPHES and UKP Lab, Technische Universit\u00e4t Darmstadt","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Technische Universit\u00e4t Darmstadt,","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333729","display_name":"Yue Zhang","orcid":"https://orcid.org/0000-0002-5214-2268"},"institutions":[{"id":"https://openalex.org/I3133055985","display_name":"Westlake University","ror":"https://ror.org/05hfa4n20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133055985"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhang","raw_affiliation_strings":["School of Engineering, Westlake University","Westlake University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Westlake University","institution_ids":["https://openalex.org/I3133055985"]},{"raw_affiliation_string":"Westlake University","institution_ids":["https://openalex.org/I3133055985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087459652","display_name":"Claire Gardent","orcid":"https://orcid.org/0000-0002-3805-6662"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210121838","display_name":"Laboratoire Lorrain de Recherche en Informatique et ses Applications","ror":"https://ror.org/02vnf0c38","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210107720","https://openalex.org/I4210121838","https://openalex.org/I4210159245","https://openalex.org/I90183372"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Claire Gardent","raw_affiliation_strings":["CNRS/LORIA, Nancy, France","CNRS, Loria, Nancy, France#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS/LORIA, Nancy, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I4210121838"]},{"raw_affiliation_string":"CNRS, Loria, Nancy, France#TAB#","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I4210121838"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027450194","display_name":"Iryna Gurevych","orcid":"https://orcid.org/0000-0003-2187-7621"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Iryna Gurevych","raw_affiliation_strings":["Research Training Group AIPHES and UKP Lab, Technische Universit\u00e4t Darmstadt","Technische Universit\u00e4t Darmstadt,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Training Group AIPHES and UKP Lab, Technische Universit\u00e4t Darmstadt","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Technische Universit\u00e4t Darmstadt,","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4021,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69533681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"589","last_page":"604"},"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/T11273","display_name":"Advanced Graph Neural Networks","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9955999851226807,"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/encode","display_name":"ENCODE","score":0.7222902178764343},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7092203497886658},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6584904193878174},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5777238607406616},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5628458261489868},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5460065603256226},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3412788510322571},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29671216011047363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1727922558784485},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1088571846485138}],"concepts":[{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.7222902178764343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7092203497886658},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6584904193878174},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5777238607406616},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5628458261489868},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5460065603256226},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3412788510322571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29671216011047363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1727922558784485},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1088571846485138},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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":8,"locations":[{"id":"doi:10.1162/tacl_a_00332","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00332","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00332/1923190/tacl_a_00332.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2001.11003","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.11003","pdf_url":"https://arxiv.org/pdf/2001.11003","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":null,"raw_type":"text"},{"id":"mag:3004074269","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2001.11003.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":"pmh:oai:HAL:hal-03020314v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03020314","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Transactions of the Association for Computational Linguistics, 2020, 8, &#x27E8;10.1162/tacl_a_00332&#x27E9;","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:5848168eeacb4ade919b9677f83ebe23","is_oa":false,"landing_page_url":"https://doaj.org/article/5848168eeacb4ade919b9677f83ebe23","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Transactions of the Association for Computational Linguistics, Vol 8 (2021)","raw_type":"article"},{"id":"pmh:oai:tubiblio.ulb.tu-darmstadt.de:121511","is_oa":false,"landing_page_url":"https://www.mitpressjournals.org/doi/full/10.1162/tacl_a_00332","pdf_url":null,"source":{"id":"https://openalex.org/S4377196390","display_name":"TUbilio (Technical University of Darmstadt)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31512782","host_organization_name":"Technische Universit\u00e4t Darmstadt","host_organization_lineage":["https://openalex.org/I31512782"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Artikel"},{"id":"doi:10.48550/arxiv.2001.11003","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.11003","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":"Preprint"},{"id":"mag:3170316695","is_oa":false,"landing_page_url":"https://virtual.2020.emnlp.org/paper_TACL.2121.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306418267","display_name":"Empirical Methods in Natural Language Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Empirical Methods in Natural Language Processing","raw_type":null}],"best_oa_location":{"id":"doi:10.1162/tacl_a_00332","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00332","pdf_url":"https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00332/1923190/tacl_a_00332.pdf","source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.49000000953674316,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3424576390","display_name":null,"funder_award_id":"GRK 1994","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G481299621","display_name":null,"funder_award_id":"GRK 1994/1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3004074269.pdf","grobid_xml":"https://content.openalex.org/works/W3004074269.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2016753842","https://openalex.org/W2101105183","https://openalex.org/W2133459682","https://openalex.org/W2157331557","https://openalex.org/W2250342921","https://openalex.org/W2250937897","https://openalex.org/W2468355276","https://openalex.org/W2525778437","https://openalex.org/W2565245743","https://openalex.org/W2604314403","https://openalex.org/W2624431344","https://openalex.org/W2786660442","https://openalex.org/W2798552002","https://openalex.org/W2798749466","https://openalex.org/W2891999054","https://openalex.org/W2918342466","https://openalex.org/W2924961378","https://openalex.org/W2931198394","https://openalex.org/W2935206035","https://openalex.org/W2946794439","https://openalex.org/W2950898568","https://openalex.org/W2951309718","https://openalex.org/W2962767366","https://openalex.org/W2962784628","https://openalex.org/W2962950136","https://openalex.org/W2963212250","https://openalex.org/W2963374482","https://openalex.org/W2963403868","https://openalex.org/W2963497309","https://openalex.org/W2963858333","https://openalex.org/W2964035651","https://openalex.org/W2964051675","https://openalex.org/W2964114465","https://openalex.org/W2964116568","https://openalex.org/W2970235396","https://openalex.org/W2970686438","https://openalex.org/W2971087717","https://openalex.org/W2971187756","https://openalex.org/W2998702685","https://openalex.org/W3003446182"],"related_works":["https://openalex.org/W3088227725","https://openalex.org/W3161315274","https://openalex.org/W2981300268","https://openalex.org/W2989985603","https://openalex.org/W3021801498","https://openalex.org/W3009525938","https://openalex.org/W3084640753","https://openalex.org/W3086430417","https://openalex.org/W2943373497","https://openalex.org/W3114713146","https://openalex.org/W3107500918","https://openalex.org/W3130747874","https://openalex.org/W3172158142","https://openalex.org/W3125118762","https://openalex.org/W2964282455","https://openalex.org/W3166679531","https://openalex.org/W2798638367","https://openalex.org/W3166984733","https://openalex.org/W2735265293","https://openalex.org/W3133818632"],"abstract_inverted_index":{"Recent":[0],"graph-to-text":[1,107],"models":[2,72,129],"generate":[3],"text":[4],"from":[5],"graph-based":[6],"data":[7],"using":[8],"either":[9],"global":[10,80],"or":[11],"local":[12,40,82],"aggregation":[13],"to":[14,57,87,102],"learn":[15,88],"node":[16,19,41,83,91],"representations.":[17],"Global":[18],"encoding":[20,42,67],"allows":[21],"explicit":[22],"communication":[23],"between":[24,46],"two":[25,106],"distant":[26],"nodes,":[27],"thereby":[28],"neglecting":[29],"graph":[30,51,77],"topology":[31],"as":[32],"all":[33],"nodes":[34,48],"are":[35],"directly":[36],"connected.":[37],"In":[38,61,93],"contrast,":[39],"considers":[43],"the":[44,50,115,121],"relations":[45],"neighbor":[47],"capturing":[49],"structure,":[52],"but":[53],"it":[54],"can":[55],"fail":[56],"capture":[58],"long-range":[59],"relations.":[60],"this":[62],"work,":[63],"we":[64,96],"gather":[65],"both":[66,79],"strategies,":[68],"proposing":[69],"novel":[70],"neural":[71],"that":[73,98],"encode":[74],"an":[75],"input":[76],"combining":[78],"and":[81,118,132],"contexts,":[84],"in":[85],"order":[86],"better":[89],"contextualized":[90],"embeddings.":[92],"our":[94,99],"experiments,":[95],"demonstrate":[97],"approaches":[100],"lead":[101],"significant":[103],"improvements":[104],"on":[105,114,120],"datasets":[108],"achieving":[109],"BLEU":[110],"scores":[111],"of":[112],"18.01":[113],"AGENDA":[116],"dataset,":[117],"63.69":[119],"WebNLG":[122],"dataset":[123],"for":[124],"seen":[125],"categories,":[126],"outperforming":[127],"state-of-the-art":[128],"by":[130],"3.7":[131],"3.1":[133],"points,":[134],"respectively.":[135],"1":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
