{"id":"https://openalex.org/W2252131007","doi":"https://doi.org/10.3115/v1/p14-3007","title":"Learning Grammar with Explicit Annotations for Subordinating Conjunctions","display_name":"Learning Grammar with Explicit Annotations for Subordinating Conjunctions","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2252131007","doi":"https://doi.org/10.3115/v1/p14-3007","mag":"2252131007"},"language":"en","primary_location":{"id":"doi:10.3115/v1/p14-3007","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-3007","pdf_url":"https://aclanthology.org/P14-3007.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 ACL 2014 Student Research Workshop","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/P14-3007.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077077784","display_name":"Dongchen Li","orcid":"https://orcid.org/0000-0001-8126-0805"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongchen Li","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062995314","display_name":"Xiantao Zhang","orcid":"https://orcid.org/0000-0002-3795-3556"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiantao Zhang","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084685506","display_name":"Xihong Wu","orcid":"https://orcid.org/0009-0004-5236-7469"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xihong Wu","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077077784"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14375374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"55"},"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":0.9994999766349792,"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":0.9890000224113464,"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/computer-science","display_name":"Computer science","score":0.8379974365234375},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7702640295028687},{"id":"https://openalex.org/keywords/subcategory","display_name":"Subcategory","score":0.728157639503479},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6069744825363159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6002817153930664},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.5907547473907471},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.43705466389656067},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4218241572380066},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.13893982768058777},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08012086153030396}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8379974365234375},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7702640295028687},{"id":"https://openalex.org/C2780617661","wikidata":"https://www.wikidata.org/wiki/Q541563","display_name":"Subcategory","level":2,"score":0.728157639503479},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6069744825363159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6002817153930664},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.5907547473907471},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.43705466389656067},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4218241572380066},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.13893982768058777},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08012086153030396},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3115/v1/p14-3007","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-3007","pdf_url":"https://aclanthology.org/P14-3007.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 ACL 2014 Student Research Workshop","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.3115/v1/p14-3007","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-3007","pdf_url":"https://aclanthology.org/P14-3007.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 ACL 2014 Student Research Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2252131007.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W108437174","https://openalex.org/W169290101","https://openalex.org/W1529490620","https://openalex.org/W2042168563","https://openalex.org/W2052816566","https://openalex.org/W2092654472","https://openalex.org/W2097606805","https://openalex.org/W2101748120","https://openalex.org/W2111536437","https://openalex.org/W2116983617","https://openalex.org/W2118584553","https://openalex.org/W2139621418","https://openalex.org/W2140351241","https://openalex.org/W2146113428","https://openalex.org/W2152561660","https://openalex.org/W2159250884","https://openalex.org/W2168194229","https://openalex.org/W2173794830","https://openalex.org/W2250416474","https://openalex.org/W2250416721","https://openalex.org/W2257859587","https://openalex.org/W2296738320","https://openalex.org/W2354689652","https://openalex.org/W2425667873","https://openalex.org/W2536430016","https://openalex.org/W2540645427","https://openalex.org/W2954762025"],"related_works":["https://openalex.org/W4226068787","https://openalex.org/W2963366818","https://openalex.org/W3157916708","https://openalex.org/W1547238018","https://openalex.org/W2178926482","https://openalex.org/W2009701419","https://openalex.org/W2148211421","https://openalex.org/W1514356479","https://openalex.org/W2168847017","https://openalex.org/W2358733850"],"abstract_inverted_index":{"Data-driven":[0],"approach":[1],"for":[2,88],"parsing":[3,141],"may":[4],"suffer":[5],"from":[6,101],"data":[7],"sparsity":[8],"when":[9],"entirely":[10],"unsupervised.":[11],"External":[12],"knowledge":[13,47,124,139],"has":[14],"been":[15],"shown":[16],"to":[17,22,40,77,106,125],"be":[18],"an":[19,84],"effective":[20],"way":[21],"alleviate":[23],"this":[24],"problem.":[25],"Subordinating":[26],"conjunctions":[27,50,61],"impose":[28],"important":[29],"constraints":[30],"on":[31,92],"Chinese":[32],"syntactic":[33,80],"structures.":[34],"This":[35],"paper":[36],"proposes":[37],"a":[38,42,99],"method":[39],"develop":[41],"grammar":[43,134],"with":[44,64],"hierarchical":[45,71,111,138],"category":[46,68],"of":[48,58,117],"subordinating":[49,60],"as":[51],"explicit":[52],"annotations.":[53],"Firstly,":[54],"each":[55,102],"part-of-speech":[56],"tag":[57],"the":[59,65,70,93,107,110,114,123,133,137,145],"is":[62,120],"annotated":[63],"most":[66],"general":[67],"in":[69,109],"knowledge.":[72,112],"Those":[73],"categories":[74,119],"are":[75],"human-defined":[76],"represent":[78],"distinct":[79],"constraints,":[81],"and":[82],"provide":[83],"appropriate":[85],"starting":[86],"point":[87],"splitting.":[89],"Secondly,":[90],"based":[91],"data-driven":[94,115],"state-split":[95],"approach,":[96],"we":[97],"establish":[98],"mapping":[100],"automatic":[103],"refined":[104],"subcategory":[105],"one":[108],"Then":[113],"splitting":[116],"these":[118],"restricted":[121],"by":[122,136],"avoid":[126],"over":[127,144],"refinement.":[128],"Experiments":[129],"demonstrate":[130],"that":[131],"constraining":[132],"learning":[135],"improves":[140],"performance":[142],"significantly":[143],"baseline.":[146]},"counts_by_year":[],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
