{"id":"https://openalex.org/W2963670884","doi":"https://doi.org/10.18653/v1/d17-1279","title":"Scientific Information Extraction with Semi-supervised Neural Tagging","display_name":"Scientific Information Extraction with Semi-supervised Neural Tagging","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2963670884","doi":"https://doi.org/10.18653/v1/d17-1279","mag":"2963670884"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1279","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1279","pdf_url":"https://www.aclweb.org/anthology/D17-1279.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1279.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074697516","display_name":"Yi Luan","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Luan","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087215613","display_name":"Mari Ostendorf","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mari Ostendorf","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082305994","display_name":"Hannaneh Hajishirzi","orcid":"https://orcid.org/0000-0002-1055-6657"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hannaneh Hajishirzi","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074697516"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":8.5134,"has_fulltext":true,"cited_by_count":78,"citation_normalized_percentile":{"value":0.98060917,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2641","last_page":"2651"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis 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/T13083","display_name":"Advanced Text Analysis 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":0.9987999796867371,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8498147130012512},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.7465163469314575},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7180463671684265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.658704400062561},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5691533088684082},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5587632060050964},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.49021750688552856},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4851987659931183},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.4737853705883026},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4733871519565582},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.46226489543914795},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38677793741226196},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.385745644569397},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.07271003723144531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8498147130012512},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.7465163469314575},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7180463671684265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.658704400062561},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5691533088684082},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5587632060050964},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.49021750688552856},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4851987659931183},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.4737853705883026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4733871519565582},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.46226489543914795},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38677793741226196},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.385745644569397},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.07271003723144531},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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:10.18653/v1/d17-1279","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1279","pdf_url":"https://www.aclweb.org/anthology/D17-1279.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1279","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1279","pdf_url":"https://www.aclweb.org/anthology/D17-1279.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320317052","display_name":"Allen Institute for Artificial Intelligence","ror":"https://ror.org/05w520734"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963670884.pdf","grobid_xml":"https://content.openalex.org/works/W2963670884.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W44474723","https://openalex.org/W172168340","https://openalex.org/W341589524","https://openalex.org/W1582518104","https://openalex.org/W1614298861","https://openalex.org/W1709989312","https://openalex.org/W1848279521","https://openalex.org/W1860935423","https://openalex.org/W1940872118","https://openalex.org/W2006834952","https://openalex.org/W2012419652","https://openalex.org/W2034222664","https://openalex.org/W2076268407","https://openalex.org/W2101964309","https://openalex.org/W2123442489","https://openalex.org/W2134767644","https://openalex.org/W2142437998","https://openalex.org/W2147880316","https://openalex.org/W2152059140","https://openalex.org/W2157979304","https://openalex.org/W2158899491","https://openalex.org/W2170973209","https://openalex.org/W2250358832","https://openalex.org/W2250539671","https://openalex.org/W2250709962","https://openalex.org/W2251320462","https://openalex.org/W2251524730","https://openalex.org/W2251771443","https://openalex.org/W2290197534","https://openalex.org/W2295800284","https://openalex.org/W2296283641","https://openalex.org/W2335122196","https://openalex.org/W2405455920","https://openalex.org/W2406184334","https://openalex.org/W2406565582","https://openalex.org/W2486109868","https://openalex.org/W2508398622","https://openalex.org/W2512877744","https://openalex.org/W2578303372","https://openalex.org/W2579538068","https://openalex.org/W2608018997","https://openalex.org/W2785349534","https://openalex.org/W2798192409","https://openalex.org/W2950577311","https://openalex.org/W2952230511","https://openalex.org/W2952729433","https://openalex.org/W2962902328","https://openalex.org/W2962903510","https://openalex.org/W2963625095","https://openalex.org/W2980197125"],"related_works":["https://openalex.org/W2806451243","https://openalex.org/W2807524541","https://openalex.org/W2806882588","https://openalex.org/W2964125981","https://openalex.org/W2605526599","https://openalex.org/W2796111924","https://openalex.org/W2806121831","https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,24,85],"problem":[4,25],"of":[5],"extracting":[6],"keyphrases":[7],"from":[8],"scientific":[9],"articles":[10],"and":[11,29,74],"categorizing":[12],"them":[13],"as":[14,26],"corresponding":[15],"to":[16,33,68],"a":[17,34,58,64],"task,":[18],"process,":[19],"or":[20],"material.":[21],"We":[22],"cast":[23],"sequence":[27],"tagging":[28,36],"introduce":[30,57],"semi-supervised":[31,60,76],"methods":[32],"neural":[35],"model,":[37],"which":[38],"builds":[39],"on":[40,84],"recent":[41],"advances":[42],"in":[43,53],"named":[44],"entity":[45],"recognition.":[46],"Since":[47],"annotated":[48],"training":[49],"data":[50,65],"is":[51],"scarce":[52],"this":[54],"domain,":[55],"we":[56],"graph-based":[59],"algorithm":[61],"together":[62],"with":[63],"selection":[66],"scheme":[67],"leverage":[69],"unannotated":[70],"articles.":[71],"Both":[72],"inductive":[73],"transductive":[75],"learning":[77],"strategies":[78],"outperform":[79],"state-of-the-art":[80],"information":[81],"extraction":[82],"performance":[83],"2017":[86],"SemEval":[87],"Task":[88],"10":[89],"ScienceIE":[90],"task.":[91]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":16},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}