{"id":"https://openalex.org/W575076247","doi":"https://doi.org/10.3115/v1/n15-1080","title":"Transforming Dependencies into Phrase Structures","display_name":"Transforming Dependencies into Phrase Structures","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W575076247","doi":"https://doi.org/10.3115/v1/n15-1080","mag":"575076247"},"language":"en","primary_location":{"id":"doi:10.3115/v1/n15-1080","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/n15-1080","pdf_url":"https://www.aclweb.org/anthology/N15-1080.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 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/N15-1080.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014554970","display_name":"Lingpeng Kong","orcid":"https://orcid.org/0000-0002-9033-2724"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingpeng Kong","raw_affiliation_strings":["School of Computer Science Carnegie Mellon University Pittsburgh, PA, USA","Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science Carnegie Mellon University Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062546146","display_name":"Alexander M. Rush","orcid":"https://orcid.org/0000-0002-9900-1606"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander M. Rush","raw_affiliation_strings":["Facebook AI Research New York, NY, USA","Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook AI Research New York, NY, USA","institution_ids":["https://openalex.org/I4210114444"]},{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088517824","display_name":"Noah A. Smith","orcid":"https://orcid.org/0000-0002-2310-6380"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noah A. Smith","raw_affiliation_strings":["School of Computer Science Carnegie Mellon University Pittsburgh, PA, USA","Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science Carnegie Mellon University Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"788","last_page":"798"},"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":0.9915000200271606,"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":0.8956905007362366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8374538421630859},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.828223466873169},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.7631189823150635},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6694849133491516},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6124622225761414},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5602836608886719},{"id":"https://openalex.org/keywords/top-down-parsing","display_name":"Top-down parsing","score":0.47945132851600647},{"id":"https://openalex.org/keywords/bottom-up-parsing","display_name":"Bottom-up parsing","score":0.4753563106060028},{"id":"https://openalex.org/keywords/parse-tree","display_name":"Parse tree","score":0.4746150076389313},{"id":"https://openalex.org/keywords/phrase-structure-rules","display_name":"Phrase structure rules","score":0.4427616596221924},{"id":"https://openalex.org/keywords/parser-combinator","display_name":"Parser combinator","score":0.42635005712509155}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8956905007362366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8374538421630859},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.828223466873169},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.7631189823150635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6694849133491516},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6124622225761414},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5602836608886719},{"id":"https://openalex.org/C42560504","wikidata":"https://www.wikidata.org/wiki/Q15419395","display_name":"Top-down parsing","level":3,"score":0.47945132851600647},{"id":"https://openalex.org/C60690694","wikidata":"https://www.wikidata.org/wiki/Q894902","display_name":"Bottom-up parsing","level":4,"score":0.4753563106060028},{"id":"https://openalex.org/C2781466058","wikidata":"https://www.wikidata.org/wiki/Q627921","display_name":"Parse tree","level":3,"score":0.4746150076389313},{"id":"https://openalex.org/C80877019","wikidata":"https://www.wikidata.org/wiki/Q7188074","display_name":"Phrase structure rules","level":3,"score":0.4427616596221924},{"id":"https://openalex.org/C118364021","wikidata":"https://www.wikidata.org/wiki/Q7139956","display_name":"Parser combinator","level":3,"score":0.42635005712509155},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3115/v1/n15-1080","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/n15-1080","pdf_url":"https://www.aclweb.org/anthology/N15-1080.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 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.cmu.edu:lti-1154","is_oa":false,"landing_page_url":"http://repository.cmu.edu/lti/162","pdf_url":null,"source":{"id":"https://openalex.org/S4306400668","display_name":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I74973139","host_organization_name":"Carnegie Mellon University","host_organization_lineage":["https://openalex.org/I74973139"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Language Technologies Institute","raw_type":"text"},{"id":"pmh:doi:10.1184/r1/6473786","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal contribution"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.720.2147","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.2147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://people.seas.harvard.edu/%7Esrush/naacl15.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.889.3972","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.889.3972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://repository.cmu.edu/cgi/viewcontent.cgi?article%3D1154%26context%3Dlti","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/6473786","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Transforming_Dependencies_into_Phrase_Structures/6473786","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.1184/r1/6473786.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/6473786.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"doi:10.3115/v1/n15-1080","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/n15-1080","pdf_url":"https://www.aclweb.org/anthology/N15-1080.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 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2399603901","display_name":"EAGER: PARTIAL: An Exploratory Study on Practical Approaches for Robust NLP Tools with Integrated Annotation Languages","funder_award_id":"1352440","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/W575076247.pdf","grobid_xml":"https://content.openalex.org/works/W575076247.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W52985019","https://openalex.org/W108437174","https://openalex.org/W181643614","https://openalex.org/W306690219","https://openalex.org/W1535015163","https://openalex.org/W1555587483","https://openalex.org/W1591659308","https://openalex.org/W1624142810","https://openalex.org/W1632114991","https://openalex.org/W1812474519","https://openalex.org/W2051818821","https://openalex.org/W2073955506","https://openalex.org/W2092654472","https://openalex.org/W2094061585","https://openalex.org/W2096044384","https://openalex.org/W2096204319","https://openalex.org/W2096466920","https://openalex.org/W2097606805","https://openalex.org/W2105644991","https://openalex.org/W2114887620","https://openalex.org/W2116957398","https://openalex.org/W2121127625","https://openalex.org/W2126433015","https://openalex.org/W2129820263","https://openalex.org/W2131698806","https://openalex.org/W2133280805","https://openalex.org/W2146502635","https://openalex.org/W2153274216","https://openalex.org/W2166451556","https://openalex.org/W2167072947","https://openalex.org/W2250562110","https://openalex.org/W2305592425","https://openalex.org/W2949972052","https://openalex.org/W2963428826","https://openalex.org/W4303698045"],"related_works":["https://openalex.org/W3143982968","https://openalex.org/W2792937288","https://openalex.org/W2164260211","https://openalex.org/W3088470625","https://openalex.org/W2952318476","https://openalex.org/W2058542628","https://openalex.org/W1908013816","https://openalex.org/W2115737371","https://openalex.org/W2004967523","https://openalex.org/W2251122646"],"abstract_inverted_index":{"We":[0,14],"present":[1],"a":[2,23],"new":[3],"algorithm":[4,27],"for":[5],"transforming":[6],"dependency":[7],"parse":[8,12],"trees":[9],"into":[10],"phrase-structure":[11],"trees.":[13],"cast":[15],"the":[16,47,50],"problem":[17],"as":[18],"structured":[19],"prediction":[20],"and":[21,34,40],"learn":[22],"statistical":[24],"model.":[25],"Our":[26],"is":[28],"faster":[29],"than":[30],"traditional":[31],"phrasestructure":[32],"parsing":[33,38,43],"achieves":[35],"90.4%":[36],"English":[37],"accuracy":[39],"82.4%":[41],"Chinese":[42],"accuracy,":[44],"near":[45],"to":[46],"state":[48],"of":[49],"art":[51],"on":[52],"both":[53],"benchmarks.":[54]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
