{"id":"https://openalex.org/W2510721067","doi":"https://doi.org/10.18653/v1/p16-3001","title":"Controlled and Balanced Dataset for Japanese Lexical Simplification","display_name":"Controlled and Balanced Dataset for Japanese Lexical Simplification","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2510721067","doi":"https://doi.org/10.18653/v1/p16-3001","mag":"2510721067"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-3001","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-3001","pdf_url":"https://www.aclweb.org/anthology/P16-3001.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL 2016 Student Research Workshop","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P16-3001.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041130402","display_name":"Tomonori Kodaira","orcid":null},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomonori Kodaira","raw_affiliation_strings":["Tokyo Metropolitan University Hino City, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University Hino City, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006117547","display_name":"Tomoyuki Kajiwara","orcid":"https://orcid.org/0000-0002-3233-4879"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoyuki Kajiwara","raw_affiliation_strings":["Tokyo Metropolitan University Hino City, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University Hino City, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061931124","display_name":"Mamoru Komachi","orcid":"https://orcid.org/0000-0003-1166-1739"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mamoru Komachi","raw_affiliation_strings":["Tokyo Metropolitan University Hino City, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University Hino City, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041130402"],"corresponding_institution_ids":["https://openalex.org/I69740276"],"apc_list":null,"apc_paid":null,"fwci":2.9993,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.92828024,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","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"}},"topics":[{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9958999752998352,"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/T12151","display_name":"Interpreting and Communication in Healthcare","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6907280087471008},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4775146543979645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3986338973045349},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3333323895931244}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6907280087471008},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4775146543979645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3986338973045349},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3333323895931244}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p16-3001","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-3001","pdf_url":"https://www.aclweb.org/anthology/P16-3001.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL 2016 Student Research Workshop","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p16-3001","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-3001","pdf_url":"https://www.aclweb.org/anthology/P16-3001.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL 2016 Student Research Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2510721067.pdf","grobid_xml":"https://content.openalex.org/works/W2510721067.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W32283444","https://openalex.org/W99857796","https://openalex.org/W106247045","https://openalex.org/W1980085274","https://openalex.org/W2070528687","https://openalex.org/W2250365808","https://openalex.org/W2251417288","https://openalex.org/W2252040661","https://openalex.org/W2523717353"],"related_works":["https://openalex.org/W2384888906","https://openalex.org/W2144190808","https://openalex.org/W2101955803","https://openalex.org/W2376314740","https://openalex.org/W2366644548","https://openalex.org/W2151447942","https://openalex.org/W2357241418","https://openalex.org/W2119214692","https://openalex.org/W2611614995","https://openalex.org/W2469626427"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,7,22],"new":[3],"dataset":[4,61,74],"for":[5,75],"evaluating":[6],"Japanese":[8,76],"lexical":[9,77],"simplification":[10,48,78,91],"method.":[11],"Previous":[12],"datasets":[13,41],"have":[14,99],"several":[15],"deficiencies.":[16],"All":[17],"of":[18,28,39,89,106],"them":[19,29],"substitute":[20],"only":[21,32],"single":[23],"target":[24],"word,":[25],"and":[26,46,72,85,101],"some":[27],"extract":[30],"sentences":[31],"from":[33,50],"newswire":[34],"corpus.":[35],"In":[36,58],"addition,":[37],"most":[38],"these":[40],"do":[42],"not":[43],"allow":[44],"ties":[45,100],"integrate":[47],"ranking":[49,92],"all":[51],"the":[52,56,63,69,87,90,104],"annotators":[53],"without":[54],"considering":[55,103],"quality.":[57],"contrast,":[59],"our":[60],"has":[62],"following":[64],"advantages:":[65],"(1)":[66],"it":[67],"is":[68,93],"first":[70],"controlled":[71],"balanced":[73],"with":[79,82],"high":[80],"correlation":[81],"human":[83],"judgment":[84],"(2)":[86],"consistency":[88],"improved":[94],"by":[95,102],"allowing":[96],"candidates":[97],"to":[98],"reliability":[105],"annotators.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
