{"id":"https://openalex.org/W4393192501","doi":"https://doi.org/10.1145/3652591","title":"Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents","display_name":"Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents","publication_year":2024,"publication_date":"2024-03-26","ids":{"openalex":"https://openalex.org/W4393192501","doi":"https://doi.org/10.1145/3652591"},"language":"en","primary_location":{"id":"doi:10.1145/3652591","doi":"https://doi.org/10.1145/3652591","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652591","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652591","source":{"id":"https://openalex.org/S4387289179","display_name":"ACM Journal on Responsible Computing","issn_l":"2832-0565","issn":["2832-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Journal on Responsible Computing","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3652591","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010062469","display_name":"Bradley Butcher","orcid":"https://orcid.org/0000-0002-4711-7826","observed_orcids":["https://orcid.org/0000-0002-4711-7826"]},"institutions":[{"id":"https://openalex.org/I162608824","display_name":"University of Sussex","ror":"https://ror.org/00ayhx656","country_code":"GB","type":"education","lineage":["https://openalex.org/I162608824"]},{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bradley Butcher","raw_affiliation_strings":["University of Sussex and The Alan Turing Institute, Brighton, UK"],"raw_orcid":"https://orcid.org/0000-0002-4711-7826","affiliations":[{"raw_affiliation_string":"University of Sussex and The Alan Turing Institute, Brighton, UK","institution_ids":["https://openalex.org/I162608824","https://openalex.org/I4210128584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080823518","display_name":"Miri Zilka","orcid":"https://orcid.org/0000-0001-9640-8139","observed_orcids":["https://orcid.org/0000-0001-9640-8139"]},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Miri Zilka","raw_affiliation_strings":["University of Cambridge, Cambridge, UK"],"raw_orcid":"https://orcid.org/0000-0001-9640-8139","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081096634","display_name":"Jiri Hron","orcid":"https://orcid.org/0009-0001-3456-7588","observed_orcids":["https://orcid.org/0009-0001-3456-7588"]},"institutions":[{"id":"https://openalex.org/I4210090411","display_name":"Google DeepMind (United Kingdom)","ror":"https://ror.org/00971b260","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090411","https://openalex.org/I4210128969"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jiri Hron","raw_affiliation_strings":["Google DeepMind, London, UK"],"raw_orcid":"https://orcid.org/0009-0001-3456-7588","affiliations":[{"raw_affiliation_string":"Google DeepMind, London, UK","institution_ids":["https://openalex.org/I4210090411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030824606","display_name":"Darren Cook","orcid":"https://orcid.org/0000-0002-6810-0281","observed_orcids":["https://orcid.org/0000-0002-6810-0281"]},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Darren Cook","raw_affiliation_strings":["Imperial College London, London, UK"],"raw_orcid":"https://orcid.org/0000-0002-6810-0281","affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042278493","display_name":"Adrian Weller","orcid":"https://orcid.org/0000-0003-1915-7158","observed_orcids":["https://orcid.org/0000-0003-1915-7158"]},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210128584","display_name":"The Alan Turing Institute","ror":"https://ror.org/035dkdb55","country_code":"GB","type":"facility","lineage":["https://openalex.org/I4210128584"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adrian Weller","raw_affiliation_strings":["University of Cambridge and The Alan Turing Institute, Cambridge, UK"],"raw_orcid":"https://orcid.org/0000-0003-1915-7158","affiliations":[{"raw_affiliation_string":"University of Cambridge and The Alan Turing Institute, Cambridge, UK","institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210128584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.6521,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.98840461,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"1","issue":"2","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.1973000019788742,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.1973000019788742,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.1891999989748001,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.1445000022649765,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/human-machine-collaboration","display_name":"human-machine collaboration","score":0.8999999761581421},{"id":"https://openalex.org/keywords/human-in-the-loop","display_name":"human-in-the-loop","score":0.7450000047683716},{"id":"https://openalex.org/keywords/information-extraction","display_name":"information extraction","score":0.9300000071525574},{"id":"https://openalex.org/keywords/unstructured-text","display_name":"unstructured text","score":0.875},{"id":"https://openalex.org/keywords/structured-information-extraction","display_name":"structured data extraction","score":0.8309999704360962},{"id":"https://openalex.org/keywords/human-validation","display_name":"human validation","score":0.6309999823570251},{"id":"https://openalex.org/keywords/automatic-extraction","display_name":"automatic extraction","score":0.5450000166893005},{"id":"https://openalex.org/keywords/criminal-justice","display_name":"criminal justice","score":0.6909999847412109},{"id":"https://openalex.org/keywords/law-enforcement","display_name":"law enforcement","score":0.5070000290870667},{"id":"https://openalex.org/keywords/precision","display_name":"precision","score":0.3199999928474426},{"id":"https://openalex.org/keywords/manual-annotation","display_name":"manual annotation","score":0.5669999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6722859144210815},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5765405893325806},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5731157064437866},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4542924761772156},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3723946213722229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3637131154537201},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3451104462146759},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08956792950630188},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.08687740564346313}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3652591","doi":"https://doi.org/10.1145/3652591","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652591","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652591","source":{"id":"https://openalex.org/S4387289179","display_name":"ACM Journal on Responsible Computing","issn_l":"2832-0565","issn":["2832-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Journal on Responsible Computing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2302.09324","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.09324","pdf_url":"https://arxiv.org/pdf/2302.09324","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:openaccess.city.ac.uk:33255","doi":null,"is_oa":true,"landing_page_url":"http://orcid.org/0000-0002-4711-7826>,","pdf_url":"https://openaccess.city.ac.uk/id/eprint/33255/1/3652591.pdf","source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2302.09324","doi":"https://doi.org/10.48550/arxiv.2302.09324","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2302.09324","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3652591","doi":"https://doi.org/10.1145/3652591","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652591","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652591","source":{"id":"https://openalex.org/S4387289179","display_name":"ACM Journal on Responsible Computing","issn_l":"2832-0565","issn":["2832-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Journal on Responsible Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5473999977111816}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1577515033","display_name":null,"funder_award_id":"EP/V025279/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1770538462","display_name":null,"funder_award_id":"ECF- 2021-429","funder_id":"https://openalex.org/F4320319993","funder_display_name":"Leverhulme Trust"},{"id":"https://openalex.org/G2439278827","display_name":"Bayesian Models and Algorithms for Fairness and Transparency","funder_award_id":"851538","funder_id":"https://openalex.org/F4320338335","funder_display_name":"H2020 European Research Council"},{"id":"https://openalex.org/G8233204778","display_name":"Turing AI Fellowship: Trustworthy Machine Learning","funder_award_id":"EP/V025279/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8401716706","display_name":null,"funder_award_id":"EP/V025279/1","funder_id":"https://openalex.org/F4320313467","funder_display_name":"Alan Turing Institute"}],"funders":[{"id":"https://openalex.org/F4320313467","display_name":"Alan Turing Institute","ror":"https://ror.org/035dkdb55"},{"id":"https://openalex.org/F4320319993","display_name":"Leverhulme Trust","ror":"https://ror.org/012mzw131"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393192501.pdf","grobid_xml":"https://content.openalex.org/works/W4393192501.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W48917825","https://openalex.org/W2071038402","https://openalex.org/W2075893342","https://openalex.org/W2098441518","https://openalex.org/W2122242424","https://openalex.org/W2133601643","https://openalex.org/W2285122028","https://openalex.org/W2338563048","https://openalex.org/W2474476938","https://openalex.org/W2565912905","https://openalex.org/W2577278960","https://openalex.org/W2626804490","https://openalex.org/W2768488789","https://openalex.org/W2894170875","https://openalex.org/W2895604144","https://openalex.org/W2899360465","https://openalex.org/W2939917690","https://openalex.org/W2949928613","https://openalex.org/W2963323070","https://openalex.org/W2964864162","https://openalex.org/W2973049411","https://openalex.org/W2974604908","https://openalex.org/W2984152228","https://openalex.org/W2990138404","https://openalex.org/W2992223989","https://openalex.org/W2995151999","https://openalex.org/W2997154779","https://openalex.org/W3008000555","https://openalex.org/W3010765510","https://openalex.org/W3015883388","https://openalex.org/W3091760893","https://openalex.org/W3094379215","https://openalex.org/W3104160712","https://openalex.org/W3104953317","https://openalex.org/W3115677442","https://openalex.org/W3120043490","https://openalex.org/W3133702157","https://openalex.org/W3147219864","https://openalex.org/W3156222574","https://openalex.org/W3160694721","https://openalex.org/W3188555706","https://openalex.org/W3196908460","https://openalex.org/W3207098447","https://openalex.org/W4210327135","https://openalex.org/W4220941542","https://openalex.org/W4224940987","https://openalex.org/W4225116079","https://openalex.org/W4235216760","https://openalex.org/W4288076015","https://openalex.org/W4288086168","https://openalex.org/W4385573087","https://openalex.org/W4388332746","https://openalex.org/W6809680140"],"related_works":["https://openalex.org/W2970507142","https://openalex.org/W4205300715","https://openalex.org/W2076578255","https://openalex.org/W2175082314","https://openalex.org/W3034565771","https://openalex.org/W7097373662","https://openalex.org/W2587364264","https://openalex.org/W1671823646","https://openalex.org/W7162402212","https://openalex.org/W2126741468"],"abstract_inverted_index":{"From":[0],"science":[1],"to":[2,37,152],"law":[3],"enforcement,":[4],"many":[5],"research":[6],"questions":[7],"are":[8,50],"answerable":[9],"only":[10,157],"by":[11,62,115],"poring":[12],"over":[13],"a":[14,93,158],"large":[15],"amount":[16],"of":[17,75,101,142,160,167],"unstructured":[18,105],"text":[19],"documents.":[20],"While":[21],"people":[22],"can":[23],"extract":[24],"information":[25],"from":[26,66,104],"such":[27],"documents":[28],"with":[29],"high":[30],"accuracy,":[31],"this":[32],"is":[33,59,109,119,128],"often":[34],"too":[35],"time-consuming":[36],"be":[38],"practical.":[39,130],"On":[40],"the":[41,71,140,143,165],"other":[42],"hand,":[43],"automated":[44,112,170],"approaches":[45],"produce":[46],"nearly-immediate":[47],"results,":[48],"but":[49,98],"not":[51,129],"reliable":[52],"enough":[53],"for":[54,87,96],"applications":[55],"where":[56,124],"near-perfect":[57],"precision":[58,150,166],"essential.":[60],"Motivated":[61],"two":[63],"use":[64,89],"cases":[65,123],"criminal":[67,134],"justice,":[68],"we":[69,91,137],"consider":[70],"benefits":[72],"and":[73,79,118,146,162],"drawbacks":[74],"various":[76],"human-only,":[77],"human\u2013machine,":[78],"machine-only":[80],"approaches.":[81],"Finding":[82],"no":[83],"tool":[84,108],"well":[85],"suited":[86],"our":[88],"cases,":[90],"develop":[92],"human-in-the-loop":[94],"method":[95],"fast":[97],"accurate":[99],"extraction":[100,113,127],"structured":[102],"data":[103],"text.":[106],"The":[107],"based":[110],"on":[111,132],"followed":[114],"human":[116,147],"validation,":[117],"particularly":[120],"useful":[121],"in":[122],"purely":[125],"manual":[126,153],"Testing":[131],"three":[133],"justice":[135],"datasets,":[136],"find":[138],"that":[139],"combination":[141],"computer":[144],"speed":[145],"understanding":[148],"yields":[149],"comparable":[151],"annotation":[154],"while":[155],"requiring":[156],"fraction":[159],"time,":[161],"significantly":[163],"outperforms":[164],"all":[168],"fully":[169],"baselines.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2024-03-27T00:00:00"}