{"id":"https://openalex.org/W4385574212","doi":"https://doi.org/10.18653/v1/2022.nllp-1.12","title":"Data-efficient end-to-end Information Extraction for Statistical Legal Analysis","display_name":"Data-efficient end-to-end Information Extraction for Statistical Legal Analysis","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385574212","doi":"https://doi.org/10.18653/v1/2022.nllp-1.12"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.nllp-1.12","pdf_url":"https://aclanthology.org/2022.nllp-1.12.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.nllp-1.12.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014643514","display_name":"Wonseok Hwang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wonseok Hwang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007329393","display_name":"Saehee Eom","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saehee Eom","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006005972","display_name":"Hanuhl Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanuhl Lee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103210762","display_name":"Hai Jin Park","orcid":"https://orcid.org/0000-0003-2523-7023"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hai Jin Park","raw_affiliation_strings":["Hanyang Univ."],"affiliations":[{"raw_affiliation_string":"Hanyang Univ.","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087565126","display_name":"Minjoon Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]},{"id":"https://openalex.org/I4210099236","display_name":"Kootenay Association for Science & Technology","ror":"https://ror.org/011pv9p44","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210099236"]}],"countries":["CA","KR"],"is_corresponding":false,"raw_author_name":"Minjoon Seo","raw_affiliation_strings":["KAIST"],"affiliations":[{"raw_affiliation_string":"KAIST","institution_ids":["https://openalex.org/I157485424","https://openalex.org/I4210099236"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.891,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":1,"citation_normalized_percentile":{"value":0.730901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":60,"max":70},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"152"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9765,"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":0.9765,"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/T10028","display_name":"Topic Modeling","score":0.9556,"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":0.63254464},{"id":"https://openalex.org/keywords/statistical-analysis","display_name":"Statistical Analysis","score":0.43399084},{"id":"https://openalex.org/keywords/legal-document","display_name":"Legal document","score":0.43029416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7538604},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7188593},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.63254464},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.61362576},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44574678},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.43399084},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43179196},{"id":"https://openalex.org/C2993995455","wikidata":"https://www.wikidata.org/wiki/Q3150005","display_name":"Legal document","level":2,"score":0.43029416},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.41409504},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3718316},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32936266},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12494728},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12447882},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.085404575},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.nllp-1.12","pdf_url":"https://aclanthology.org/2022.nllp-1.12.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.01692","pdf_url":"http://arxiv.org/pdf/2211.01692","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.nllp-1.12","pdf_url":"https://aclanthology.org/2022.nllp-1.12.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":17,"referenced_works":["https://openalex.org/W2601470260","https://openalex.org/W2973727699","https://openalex.org/W2979826702","https://openalex.org/W3117174129","https://openalex.org/W3125259815","https://openalex.org/W3133671674","https://openalex.org/W3135190223","https://openalex.org/W3156133475","https://openalex.org/W3216533828","https://openalex.org/W4205661396","https://openalex.org/W4206785765","https://openalex.org/W4225641672","https://openalex.org/W4282813826","https://openalex.org/W4285184770","https://openalex.org/W4288089799","https://openalex.org/W4309444617","https://openalex.org/W4381802325"],"related_works":["https://openalex.org/W4364383453","https://openalex.org/W4319453497","https://openalex.org/W2889874405","https://openalex.org/W2725657302","https://openalex.org/W2393978999","https://openalex.org/W2379157006","https://openalex.org/W2367301249","https://openalex.org/W2352337653","https://openalex.org/W2153799433","https://openalex.org/W1788528807"],"abstract_inverted_index":{"Legal":[0],"practitioners":[1],"often":[2,48],"face":[3],"a":[4,90],"vast":[5],"amount":[6],"of":[7,23,43,109,182],"documents.":[8,85],"Lawyers,":[9],"for":[10,13,83],"instance,":[11],"search":[12,30],"appropriate":[14],"precedents":[15,25,115,167],"favorable":[16],"to":[17,56,64,99,129],"their":[18,70],"clients,":[19],"while":[20],"the":[21,41,130,169,179],"number":[22,42],"legal":[24,29,84,184],"is":[26,47],"ever-growing.":[27],"Although":[28],"engines":[31],"can":[32,95,121],"assist":[33],"finding":[34],"individual":[35],"target":[36],"documents":[37],"and":[38,53,142,162],"narrowing":[39],"down":[40],"candidates,":[44],"retrieved":[45],"information":[46,65,79,172],"presented":[49],"as":[50,89,134,136],"unstructured":[51],"text":[52],"users":[54],"have":[55],"examine":[57],"each":[58],"document":[59],"thoroughly":[60],"which":[61],"could":[62],"lead":[63],"overloading.":[66],"This":[67],"also":[68],"makes":[69],"statistical":[71,153],"analysis":[72,154],"challenging.":[73],"Here,":[74],"we":[75],"present":[76],"an":[77],"end-to-end":[78],"extraction":[80],"(IE)":[81],"system":[82,94,120,176],"By":[86],"formulating":[87],"IE":[88,111,119,175],"generation":[91],"task,":[92],"our":[93,118,152,174],"be":[96],"easily":[97],"applied":[98],"various":[100],"tasks":[101,112],"without":[102],"domain-specific":[103],"engineering":[104],"effort.":[105],"The":[106],"experimental":[107],"results":[108],"four":[110],"on":[113,126,146,155],"Korean":[114,183],"shows":[116],"that":[117],"achieve":[122],"competent":[123],"scores":[124],"(-2.3":[125],"average)":[127,147],"compared":[128],"rule-based":[131],"baseline":[132],"with":[133,148,165],"few":[135],"50":[137],"training":[138],"examples":[139],"per":[140],"task":[141],"higher":[143],"score":[144],"(+5.4":[145],"200":[149],"examples.":[150],"Finally,":[151],"two":[156],"case":[157],"categories":[158],"\u2014":[159,164],"drunk":[160],"driving":[161],"fraud":[163],"35k":[166],"reveals":[168],"resulting":[170],"structured":[171],"from":[173],"faithfully":[177],"reflects":[178],"macroscopic":[180],"features":[181],"system.":[185]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4385574212","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2024-12-13T19:22:17.774979","created_date":"2023-08-05"}