{"id":"https://openalex.org/W4392445457","doi":"https://doi.org/10.1145/3639233.3639334","title":"Semantic Role Labeling for Japanese Using Span-Based Models","display_name":"Semantic Role Labeling for Japanese Using Span-Based Models","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4392445457","doi":"https://doi.org/10.1145/3639233.3639334"},"language":"en","primary_location":{"id":"doi:10.1145/3639233.3639334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639334","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639334","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094066177","display_name":"Callum Kodai Tulloch","orcid":"https://orcid.org/0009-0004-3084-3364"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Callum Kodai Tulloch","raw_affiliation_strings":["Graduate School of Environmental,Life Natural Science and Technology, Okayama University, Japan"],"raw_orcid":"https://orcid.org/0009-0004-3084-3364","affiliations":[{"raw_affiliation_string":"Graduate School of Environmental,Life Natural Science and Technology, Okayama University, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072934270","display_name":"Koichi Takeuchi","orcid":"https://orcid.org/0009-0000-4926-0661"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koichi Takeuchi","raw_affiliation_strings":["Graduate School of Environmental,Life Natural Science and Technology, Okayama University, Japan"],"raw_orcid":"https://orcid.org/0009-0000-4926-0661","affiliations":[{"raw_affiliation_string":"Graduate School of Environmental,Life Natural Science and Technology, Okayama University, Japan","institution_ids":["https://openalex.org/I163770644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I163770644"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51186468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"161","last_page":"167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/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/T13629","display_name":"Text Readability and Simplification","score":0.9876999855041504,"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/span","display_name":"Span (engineering)","score":0.7636156678199768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7571840286254883},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6789931058883667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6389433145523071},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6116656064987183},{"id":"https://openalex.org/keywords/semantic-role-labeling","display_name":"Semantic role labeling","score":0.5571783185005188},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5112650394439697},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.507977306842804},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.4501186013221741}],"concepts":[{"id":"https://openalex.org/C2778753569","wikidata":"https://www.wikidata.org/wiki/Q1960395","display_name":"Span (engineering)","level":2,"score":0.7636156678199768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7571840286254883},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6789931058883667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6389433145523071},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6116656064987183},{"id":"https://openalex.org/C67277372","wikidata":"https://www.wikidata.org/wiki/Q7449085","display_name":"Semantic role labeling","level":3,"score":0.5571783185005188},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5112650394439697},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.507977306842804},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.4501186013221741},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3639233.3639334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639334","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3639233.3639334","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639334","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639334","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4168960317","display_name":"Development of a method for synonymous expressions based on annotated predicate-argument graph data and its application to automatic essay scoring","funder_award_id":"22K00530","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392445457.pdf","grobid_xml":"https://content.openalex.org/works/W4392445457.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2115792525","https://openalex.org/W2158847908","https://openalex.org/W2250726251","https://openalex.org/W2740295529","https://openalex.org/W2740765036","https://openalex.org/W2798956534","https://openalex.org/W2962803243","https://openalex.org/W2963560594","https://openalex.org/W3034323081"],"related_works":["https://openalex.org/W2067317451","https://openalex.org/W4229054622","https://openalex.org/W4283651310","https://openalex.org/W4283803146","https://openalex.org/W2154771632","https://openalex.org/W4283792424","https://openalex.org/W4211085505","https://openalex.org/W3122478268","https://openalex.org/W2084758217","https://openalex.org/W408804804"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,65,116,120,131,135,150,163],"span-based":[3,62,106,147],"model":[4,117,132],"for":[5,124,137,165],"Japanese":[6,48,66,151],"Semantic":[7],"Role":[8],"Labeling":[9],"(SRL)":[10],"with":[11,72,86],"deep":[12],"neural":[13],"networks.":[14],"Most":[15],"previous":[16,44],"studies":[17,45],"of":[18,42,89,146,175],"semantic":[19,73,82,90,121,167],"role":[20,74,91,122,168],"labeling":[21],"have":[22],"been":[23],"conducted":[24],"in":[25,38,57,177],"English,":[26],"however,":[27],"it":[28],"is":[29,70,115,130],"not":[30],"clear":[31],"that":[32,99,118,133,158],"previously":[33],"proposed":[34],"models":[35,63,148],"are":[36,84,100,109],"effective":[37],"Japanese.":[39],"Besides,":[40],"most":[41],"the":[43,52,105,128,143,159,171,180],"relating":[46],"to":[47,64,102,149,179],"SRL":[49,54,152],"focus":[50],"on":[51],"dependency-based":[53],"task.":[55,153],"Thus,":[56,140],"this":[58],"paper,":[59],"we":[60,141],"apply":[61,142],"corpus":[67],"NPCMJ-PT":[68],"which":[69,161],"annotated":[71],"labels":[75,92],"and":[76,97,127],"has":[77],"about":[78],"52,500":[79],"entries.":[80],"The":[81,154],"roles":[83],"defined":[85],"32":[87],"types":[88,145],"such":[93],"as":[94],"Arg0,":[95],"Arg1,":[96],"ArgM-LOC":[98],"similar":[101],"PropBank.":[103],"In":[104],"models,":[107],"there":[108],"two":[110,144],"primary":[111],"modeling":[112],"approaches.":[113],"One":[114],"estimates":[119,134,162],"label":[123],"each":[125,138,166],"span,":[126],"other":[129,181],"span":[136,164],"label.":[139],"experimental":[155],"results":[156],"demonstrate":[157],"model,":[160],"label,":[169],"achieved":[170],"highest":[172],"F1":[173],"score":[174],"77.54,":[176],"comparison":[178],"model.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}