{"id":"https://openalex.org/W2145453687","doi":null,"title":"Collective Cross-Document Relation Extraction Without Labelled Data","display_name":"Collective Cross-Document Relation Extraction Without Labelled Data","publication_year":2010,"publication_date":"2010-10-09","ids":{"openalex":"https://openalex.org/W2145453687","mag":"2145453687"},"language":"en","primary_location":{"id":"pmh:oai:works.bepress.com:andrew_mccallum-1123","doi":null,"is_oa":true,"landing_page_url":"https://works.bepress.com/andrew_mccallum/74","pdf_url":"https://works.bepress.com/andrew_mccallum/74","source":{"id":"https://openalex.org/S4306402240","display_name":"ScholarWorks@UMassAmherst (University of Massachusetts Amherst)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I24603500","host_organization_name":"University of Massachusetts Amherst","host_organization_lineage":["https://openalex.org/I24603500"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Andrew McCallum","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://works.bepress.com/andrew_mccallum/74","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041037769","display_name":"Limin Yao","orcid":"https://orcid.org/0009-0000-5245-8353","observed_orcids":["https://orcid.org/0009-0000-5245-8353"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Limin Yao","raw_affiliation_strings":["University of Massachusetts: Amherst#TAB#"],"raw_orcid":"https://orcid.org/0009-0000-5245-8353","affiliations":[{"raw_affiliation_string":"University of Massachusetts: Amherst#TAB#","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101404695","display_name":"Sebastian Riedel","orcid":"https://orcid.org/0000-0002-3655-2486","observed_orcids":["https://orcid.org/0000-0002-3655-2486"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sebastian Riedel","raw_affiliation_strings":["University of Massachusetts: Amherst#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-3655-2486","affiliations":[{"raw_affiliation_string":"University of Massachusetts: Amherst#TAB#","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107835063","display_name":"Andrew McCallum","orcid":"https://orcid.org/0000-0003-2843-6992","observed_orcids":["https://orcid.org/0000-0003-2843-6992"]},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew McCallum","raw_affiliation_strings":["University of Massachusetts: Amherst#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts: Amherst#TAB#","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":12.6849,"has_fulltext":true,"cited_by_count":114,"citation_normalized_percentile":{"value":0.98941137,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1013","last_page":"1023"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9448000192642212,"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":0.9448000192642212,"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":0.04899999871850014,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.0013000000035390258,"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/entity-identification","display_name":"entity identification","score":0.5540000200271606},{"id":"https://openalex.org/keywords/remote-supervision","display_name":"distant supervision","score":0.7860000133514404},{"id":"https://openalex.org/keywords/factor-graphs","display_name":"factor graphs","score":0.7549999952316284},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.9409999847412109},{"id":"https://openalex.org/keywords/joint-inference","display_name":"joint inference","score":0.6029999852180481},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"knowledge base","score":0.6340000033378601},{"id":"https://openalex.org/keywords/freebase","display_name":"Freebase","score":0.8840000033378601},{"id":"https://openalex.org/keywords/out-of-domain-generalization","display_name":"out-of-domain generalization","score":0.7699999809265137},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"semi-supervised learning","score":0.5720000267028809}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8548399209976196},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.8308277726173401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8292927742004395},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7208966612815857},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.622616171836853},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.596446692943573},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5845903158187866},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5839051008224487},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5406380295753479},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5042663812637329},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46399495005607605},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.4598664939403534},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.42604148387908936},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3809082806110382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3314698338508606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20934242010116577},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.203337162733078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09547728300094604},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.08053410053253174},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:works.bepress.com:andrew_mccallum-1123","doi":null,"is_oa":true,"landing_page_url":"https://works.bepress.com/andrew_mccallum/74","pdf_url":"https://works.bepress.com/andrew_mccallum/74","source":{"id":"https://openalex.org/S4306402240","display_name":"ScholarWorks@UMassAmherst (University of Massachusetts Amherst)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I24603500","host_organization_name":"University of Massachusetts Amherst","host_organization_lineage":["https://openalex.org/I24603500"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Andrew McCallum","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.186.3058","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.3058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aclweb.org/anthology-new/D/D10/D10-1099.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.366.9397","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.366.9397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://maroo.cs.umass.edu/pub/web/getpdf.php?id=957","raw_type":"text"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1367735","doi":null,"is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1367735/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: (pp. pp. 1013-1023). (2010)","raw_type":"Proceedings paper"},{"id":"mag:2145453687","doi":null,"is_oa":false,"landing_page_url":"http://ciir-publications.cs.umass.edu/pub/web/getpdf.php?id=957","pdf_url":null,"source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":"Empirical Methods in Natural Language Processing","raw_type":null}],"best_oa_location":{"id":"pmh:oai:works.bepress.com:andrew_mccallum-1123","doi":null,"is_oa":true,"landing_page_url":"https://works.bepress.com/andrew_mccallum/74","pdf_url":"https://works.bepress.com/andrew_mccallum/74","source":{"id":"https://openalex.org/S4306402240","display_name":"ScholarWorks@UMassAmherst (University of Massachusetts Amherst)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I24603500","host_organization_name":"University of Massachusetts Amherst","host_organization_lineage":["https://openalex.org/I24603500"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Andrew McCallum","raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3780657347","display_name":"RI-Medium: Collaborative Research: Dynamically-Structured Conditional Random Fields for Complex, Natural Domains","funder_award_id":"0803847","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5105226944","display_name":null,"funder_award_id":"FA8750-09-C-0181","funder_id":"https://openalex.org/F4320338294","funder_display_name":"Air Force Research Laboratory"},{"id":"https://openalex.org/G7704502625","display_name":"ITR:     Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis","funder_award_id":"0326249","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309370","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10"},{"id":"https://openalex.org/F4320311089","display_name":"National Security Agency","ror":"https://ror.org/0047bvr32"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332815","display_name":"Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2145453687.pdf","grobid_xml":"https://content.openalex.org/works/W2145453687.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W161217653","https://openalex.org/W1497611705","https://openalex.org/W1604644367","https://openalex.org/W1714704734","https://openalex.org/W1866795174","https://openalex.org/W1894162078","https://openalex.org/W1954715867","https://openalex.org/W1981082061","https://openalex.org/W1984626158","https://openalex.org/W2008652694","https://openalex.org/W2020999234","https://openalex.org/W2038037963","https://openalex.org/W2060716942","https://openalex.org/W2094728533","https://openalex.org/W2096765155","https://openalex.org/W2107598941","https://openalex.org/W2120814856","https://openalex.org/W2125972432","https://openalex.org/W2132655161","https://openalex.org/W2147880316","https://openalex.org/W2150588363","https://openalex.org/W2170694982","https://openalex.org/W2465041517","https://openalex.org/W3158986179"],"related_works":["https://openalex.org/W1604644367","https://openalex.org/W2107598941","https://openalex.org/W2609844752","https://openalex.org/W2994001811","https://openalex.org/W4385570583","https://openalex.org/W4385574199","https://openalex.org/W4400910169","https://openalex.org/W4402670873","https://openalex.org/W3091683050","https://openalex.org/W3091518332"],"abstract_inverted_index":{"We":[0,31,71],"present":[1],"a":[2,37,81,112],"novel":[3],"approach":[4,74],"to":[5,35,66,98],"relation":[6,25,42],"extraction":[7,26,43],"that":[8,64],"integrates":[9],"information":[10],"across":[11],"documents,":[12],"performs":[13],"global":[14],"inference":[15,57],"and":[16,27,80,124,134],"requires":[17],"no":[18,109],"labelled":[19],"text.":[20],"In":[21],"particular,":[22],"we":[23,58,118],"tackle":[24],"entity":[28],"identification":[29],"jointly.":[30],"use":[32],"distant":[33],"supervision":[34],"train":[36],"factor":[38],"graph":[39],"model":[40,96],"for":[41,76,143],"based":[44],"on":[45],"an":[46,60,77,103],"existing":[47],"knowledge":[48],"base":[49],"(Freebase,":[50],"derived":[51],"in":[52,127],"parts":[53],"from":[54,121],"Wikipedia).":[55],"For":[56,90,114],"run":[59],"efficient":[61],"Gibbs":[62],"sampler":[63],"leads":[65,97],"linear":[67],"time":[68],"joint":[69,95,122],"inference.":[70],"evaluate":[72],"our":[73,94],"both":[75],"in-domain":[78,92],"(Wikipedia)":[79],"more":[82],"realistic":[83],"out-of-domain":[84,116],"(New":[85],"York":[86],"Times":[87],"Corpus)":[88],"setting.":[89],"the":[91,115,132,137],"setting,":[93],"4%":[99],"higher":[100],"precision":[101,128],"than":[102],"isolated":[104,138],"local":[105],"approach,":[106],"but":[107],"has":[108],"advantage":[110],"over":[111,131,136],"pipeline.":[113],"data,":[117],"benefit":[119],"strongly":[120],"modelling,":[123],"observe":[125],"improvements":[126],"of":[129],"13%":[130],"pipeline,":[133],"15%":[135],"baseline.":[139],"\u00a9":[140],"2010":[141],"Association":[142],"Computational":[144],"Linguistics.":[145]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":14},{"year":2013,"cited_by_count":13},{"year":2012,"cited_by_count":15}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}