{"id":"https://openalex.org/W2759996821","doi":"https://doi.org/10.18653/v1/d17-1133","title":"Learning Contextually Informed Representations for Linear-Time Discourse Parsing","display_name":"Learning Contextually Informed Representations for Linear-Time Discourse Parsing","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2759996821","doi":"https://doi.org/10.18653/v1/d17-1133","mag":"2759996821"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1133","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1133","pdf_url":"https://www.aclweb.org/anthology/D17-1133.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 Language Processing","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/D17-1133.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355692","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7300-9215"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041024491","display_name":"Mirella Lapata","orcid":"https://orcid.org/0000-0002-2107-1516"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mirella Lapata","raw_affiliation_strings":["Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100355692"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8341333866119385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7863423824310303},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.646081268787384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6121896505355835},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5408087968826294},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.519388735294342},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.518527626991272},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5010926723480225},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.487255722284317},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1848621964454651},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1693960726261139},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11437693238258362}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8341333866119385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7863423824310303},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.646081268787384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6121896505355835},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5408087968826294},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.519388735294342},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.518527626991272},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5010926723480225},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.487255722284317},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1848621964454651},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1693960726261139},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11437693238258362},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/d17-1133","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1133","pdf_url":"https://www.aclweb.org/anthology/D17-1133.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 Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/50207d35-c869-4986-9093-1e14a2834084","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/50207d35-c869-4986-9093-1e14a2834084","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1133","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1133","pdf_url":"https://www.aclweb.org/anthology/D17-1133.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 Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2759996821.pdf","grobid_xml":"https://content.openalex.org/works/W2759996821.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W64910274","https://openalex.org/W332673702","https://openalex.org/W1497300277","https://openalex.org/W1533861849","https://openalex.org/W1614298861","https://openalex.org/W1869752048","https://openalex.org/W1889268436","https://openalex.org/W1895577753","https://openalex.org/W1967977424","https://openalex.org/W2005708641","https://openalex.org/W2028651375","https://openalex.org/W2044599851","https://openalex.org/W2045738181","https://openalex.org/W2046436395","https://openalex.org/W2064675550","https://openalex.org/W2069684104","https://openalex.org/W2120262106","https://openalex.org/W2123442489","https://openalex.org/W2130942839","https://openalex.org/W2134036914","https://openalex.org/W2135336649","https://openalex.org/W2154407881","https://openalex.org/W2165887782","https://openalex.org/W2166957049","https://openalex.org/W2176475152","https://openalex.org/W2250767751","https://openalex.org/W2251211118","https://openalex.org/W2251293245","https://openalex.org/W2251454145","https://openalex.org/W2252267789","https://openalex.org/W2301095666","https://openalex.org/W2512597464","https://openalex.org/W2563495010","https://openalex.org/W2565349465","https://openalex.org/W2949952998","https://openalex.org/W2950577311","https://openalex.org/W2963069010","https://openalex.org/W4250641076","https://openalex.org/W4253555784"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W2087343574"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,97,102],"RST":[3],"discourse":[4,24,57],"parsing":[5],"have":[6],"focused":[7],"on":[8,40,60,87],"two":[9],"modeling":[10],"paradigms:":[11],"(a)":[12],"high":[13],"order":[14],"parsers":[15,33],"which":[16,34,63],"jointly":[17],"predict":[18],"the":[19,23,26,98,103],"tree":[20],"structure":[21],"of":[22,55,100],"and":[25,70,105],"relations":[27],"it":[28],"encodes;":[29],"or":[30],"(b)":[31],"lineartime":[32],"are":[35],"efficient":[36,92],"but":[37],"mostly":[38],"based":[39,59],"local":[41],"features.":[42],"In":[43],"this":[44],"work,":[45],"we":[46],"propose":[47],"a":[48,52],"linear-time":[49],"parser":[50,82],"with":[51],"novel":[53],"way":[54],"representing":[56],"constituents":[58],"neural":[61],"networks":[62],"takes":[64],"into":[65],"account":[66],"global":[67],"contextual":[68],"information":[69],"is":[71],"able":[72],"to":[73],"capture":[74],"long-distance":[75],"dependencies.":[76],"Experimental":[77],"results":[78],"show":[79],"that":[80],"our":[81],"obtains":[83],"state-of-the":[84],"art":[85],"performance":[86],"benchmark":[88],"datasets,":[89],"while":[90],"being":[91],"(with":[93],"time":[94],"complexity":[95],"linear":[96],"number":[99],"sentences":[101],"document)":[104],"requiring":[106],"minimal":[107],"feature":[108],"engineering.":[109]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
