{"id":"https://openalex.org/W2970713124","doi":"https://doi.org/10.18653/v1/d19-1594","title":"Text Genre and Training Data Size in Human-like Parsing","display_name":"Text Genre and Training Data Size in Human-like Parsing","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970713124","doi":"https://doi.org/10.18653/v1/d19-1594","mag":"2970713124"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d19-1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1594","pdf_url":"https://www.aclweb.org/anthology/D19-1594.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 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D19-1594.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054978902","display_name":"John Hale","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090411","display_name":"Google DeepMind (United Kingdom)","ror":"https://ror.org/00971b260","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090411","https://openalex.org/I4210128969"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Hale","raw_affiliation_strings":["DeepMind / London"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepMind / London","institution_ids":["https://openalex.org/I4210090411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069646529","display_name":"Adhiguna Kuncoro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090411","display_name":"Google DeepMind (United Kingdom)","ror":"https://ror.org/00971b260","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090411","https://openalex.org/I4210128969"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Adhiguna Kuncoro","raw_affiliation_strings":["DeepMind / London"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepMind / London","institution_ids":["https://openalex.org/I4210090411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013958949","display_name":"Keith Hall","orcid":"https://orcid.org/0000-0002-0977-6572"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keith Hall","raw_affiliation_strings":["Google Research / New York"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research / New York","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111222692","display_name":"Chris Dyer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090411","display_name":"Google DeepMind (United Kingdom)","ror":"https://ror.org/00971b260","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090411","https://openalex.org/I4210128969"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chris Dyer","raw_affiliation_strings":["DeepMind / London"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DeepMind / London","institution_ids":["https://openalex.org/I4210090411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039799789","display_name":"Jonathan Brennan","orcid":"https://orcid.org/0000-0002-3639-350X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Brennan","raw_affiliation_strings":["University of Michigan / Ann Arbor"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan / Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5845","last_page":"5851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9950000047683716,"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/parsing","display_name":"Parsing","score":0.8075106143951416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7628185153007507},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.574725329875946},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5204777717590332},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5175697207450867},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.4154432415962219},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4136737585067749},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.12261316180229187},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08534544706344604}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8075106143951416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628185153007507},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.574725329875946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5204777717590332},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5175697207450867},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.4154432415962219},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4136737585067749},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.12261316180229187},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08534544706344604},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d19-1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1594","pdf_url":"https://www.aclweb.org/anthology/D19-1594.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 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d19-1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-1594","pdf_url":"https://www.aclweb.org/anthology/D19-1594.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 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8899999856948853}],"awards":[{"id":"https://openalex.org/G7682400881","display_name":"US-French Collaboration: Collaborative Research: Neuro-Computational Models of Natural Language","funder_award_id":"1607441","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970713124.pdf","grobid_xml":"https://content.openalex.org/works/W2970713124.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W98423455","https://openalex.org/W199541590","https://openalex.org/W1507020546","https://openalex.org/W1567277581","https://openalex.org/W1632114991","https://openalex.org/W1716844867","https://openalex.org/W1905522558","https://openalex.org/W2054125330","https://openalex.org/W2055916244","https://openalex.org/W2064675550","https://openalex.org/W2067575282","https://openalex.org/W2105103433","https://openalex.org/W2117278770","https://openalex.org/W2120354757","https://openalex.org/W2124416056","https://openalex.org/W2134036914","https://openalex.org/W2137806537","https://openalex.org/W2139621418","https://openalex.org/W2161222299","https://openalex.org/W2163568299","https://openalex.org/W2168979204","https://openalex.org/W2203714058","https://openalex.org/W2252050256","https://openalex.org/W2559671171","https://openalex.org/W2626967794","https://openalex.org/W2795342569","https://openalex.org/W2825244390","https://openalex.org/W2896457183","https://openalex.org/W2909386406","https://openalex.org/W2911681509","https://openalex.org/W2918996109","https://openalex.org/W2921890305","https://openalex.org/W2949952998","https://openalex.org/W2962690139","https://openalex.org/W2962941914","https://openalex.org/W2963073938","https://openalex.org/W2963341956","https://openalex.org/W2963751529","https://openalex.org/W2964335542","https://openalex.org/W2977559956","https://openalex.org/W3146885639"],"related_works":["https://openalex.org/W579810227","https://openalex.org/W2952780262","https://openalex.org/W2979495269","https://openalex.org/W2392917763","https://openalex.org/W2083429127","https://openalex.org/W2358855848","https://openalex.org/W2142145894","https://openalex.org/W4381248170","https://openalex.org/W3189621521","https://openalex.org/W2173794830"],"abstract_inverted_index":{"John":[0],"Hale,":[1],"Adhiguna":[2],"Kuncoro,":[3],"Keith":[4],"Hall,":[5],"Chris":[6],"Dyer,":[7],"Jonathan":[8],"Brennan.":[9],"Proceedings":[10],"of":[11],"the":[12,23],"2019":[13],"Conference":[14,27],"on":[15,28],"Empirical":[16],"Methods":[17],"in":[18],"Natural":[19,29],"Language":[20,30],"Processing":[21,31],"and":[22],"9th":[24],"International":[25],"Joint":[26],"(EMNLP-IJCNLP).":[32],"2019.":[33]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}