{"id":"https://openalex.org/W2805715057","doi":"https://doi.org/10.18653/v1/s18-2021","title":"Deep Affix Features Improve Neural Named Entity Recognizers","display_name":"Deep Affix Features Improve Neural Named Entity Recognizers","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2805715057","doi":"https://doi.org/10.18653/v1/s18-2021","mag":"2805715057"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s18-2021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-2021","pdf_url":"https://www.aclweb.org/anthology/S18-2021.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 Seventh Joint Conference on Lexical and\n          Computational Semantics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S18-2021.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101500443","display_name":"Vikas Yadav","orcid":"https://orcid.org/0000-0002-8536-2822"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vikas Yadav","raw_affiliation_strings":["School of Information,"],"affiliations":[{"raw_affiliation_string":"School of Information,","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053335951","display_name":"Rebecca Sharp","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rebecca Sharp","raw_affiliation_strings":["Dept. of Computer Science University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068978543","display_name":"Steven Bethard","orcid":"https://orcid.org/0000-0001-9560-6491"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steven Bethard","raw_affiliation_strings":["School of Information,"],"affiliations":[{"raw_affiliation_string":"School of Information,","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101500443"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5608,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.9567764,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"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/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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T11719","display_name":"Data Quality and Management","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.897659182548523},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.8549301624298096},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6883004903793335},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6881952881813049},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6786237955093384},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5713247656822205},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.5569947957992554},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5360453724861145},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5113101005554199},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43399786949157715},{"id":"https://openalex.org/keywords/affix","display_name":"Affix","score":0.4245617985725403},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.422486275434494},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12406271696090698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.897659182548523},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.8549301624298096},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6883004903793335},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6881952881813049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6786237955093384},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5713247656822205},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.5569947957992554},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5360453724861145},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5113101005554199},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43399786949157715},{"id":"https://openalex.org/C2778428490","wikidata":"https://www.wikidata.org/wiki/Q62155","display_name":"Affix","level":2,"score":0.4245617985725403},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.422486275434494},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12406271696090698},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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:10.18653/v1/s18-2021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-2021","pdf_url":"https://www.aclweb.org/anthology/S18-2021.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 Seventh Joint Conference on Lexical and\n          Computational Semantics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s18-2021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-2021","pdf_url":"https://www.aclweb.org/anthology/S18-2021.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 Seventh Joint Conference on Lexical and\n          Computational Semantics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2805715057.pdf","grobid_xml":"https://content.openalex.org/works/W2805715057.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W68293321","https://openalex.org/W886998232","https://openalex.org/W1486886935","https://openalex.org/W1992004647","https://openalex.org/W1995249715","https://openalex.org/W2015079391","https://openalex.org/W2064675550","https://openalex.org/W2140016149","https://openalex.org/W2144578941","https://openalex.org/W2145075080","https://openalex.org/W2148488766","https://openalex.org/W2168041406","https://openalex.org/W2192572088","https://openalex.org/W2251012068","https://openalex.org/W2251559320","https://openalex.org/W2251593362","https://openalex.org/W2296283641","https://openalex.org/W2401534278","https://openalex.org/W2493916176","https://openalex.org/W2527896214","https://openalex.org/W2560939934","https://openalex.org/W2604986524","https://openalex.org/W2725541287","https://openalex.org/W2950938254","https://openalex.org/W2952087486","https://openalex.org/W2962902328","https://openalex.org/W2963208801","https://openalex.org/W2963625095","https://openalex.org/W4238967175"],"related_works":["https://openalex.org/W2560552153","https://openalex.org/W4318200119","https://openalex.org/W2339162616","https://openalex.org/W4313038312","https://openalex.org/W3016924872","https://openalex.org/W2356412146","https://openalex.org/W2181632851","https://openalex.org/W4223625727","https://openalex.org/W2376293157","https://openalex.org/W4384447452"],"abstract_inverted_index":{"We":[0,29,109],"propose":[1],"a":[2,17,112],"practical":[3],"model":[4],"for":[5],"named":[6],"entity":[7],"recognition":[8],"(NER)":[9],"that":[10,40],"combines":[11],"word":[12],"and":[13,24,35,38,53,55,97],"character-level":[14],"information":[15],"with":[16,122],"specific":[18],"learned":[19],"representation":[20],"of":[21,26,44,68,89,106],"the":[22,27,45,49,66,69,90,94,98,107,116],"prefixes":[23],"suffixes":[25],"word.":[28],"apply":[30],"this":[31],"approach":[32],"to":[33],"multilingual":[34],"multi-domain":[36],"NER":[37,59,120],"show":[39,79],"it":[41],"achieves":[42],"state":[43,67,88,105],"art":[46,70,91],"results":[47,92,101],"on":[48,73,81,93,115],"CoNLL":[50,56],"2002":[51],"Spanish":[52],"Dutch":[54],"2003":[57],"German":[58],"datasets,":[60],"consistently":[61],"achieving":[62,87],"1.5-2.3":[63],"percent":[64],"over":[65],"without":[71],"relying":[72],"any":[74],"dictionary":[75],"features.":[76],"Additionally,":[77],"we":[78],"improvement":[80],"SemEval":[82],"2013":[83],"task":[84],"9.1":[85],"DrugNER,":[86],"MedLine":[95],"dataset":[96,121],"second":[99],"best":[100],"overall":[102],"(-1.3%":[103],"from":[104],"art).":[108],"also":[110],"establish":[111],"new":[113],"benchmark":[114],"I2B2":[117],"2010":[118],"Clinical":[119],"84.70":[123],"F-score.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
