{"id":"https://openalex.org/W2741390671","doi":"https://doi.org/10.18653/v1/p17-1111","title":"Neural Joint Model for Transition-based Chinese Syntactic Analysis","display_name":"Neural Joint Model for Transition-based Chinese Syntactic Analysis","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2741390671","doi":"https://doi.org/10.18653/v1/p17-1111","mag":"2741390671"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p17-1111","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1111","pdf_url":"https://www.aclweb.org/anthology/P17-1111.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P17-1111.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073732915","display_name":"Shuhei Kurita","orcid":"https://orcid.org/0000-0001-7415-3120"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shuhei Kurita","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102867777","display_name":"Daisuke Kawahara","orcid":"https://orcid.org/0000-0002-3598-1027"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Kawahara","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028836340","display_name":"Sadao Kurohashi","orcid":"https://orcid.org/0000-0001-5398-8399"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sadao Kurohashi","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073732915"],"corresponding_institution_ids":["https://openalex.org/I22299242"],"apc_list":null,"apc_paid":null,"fwci":5.2655,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.96423983,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1204","last_page":"1214"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9908000230789185,"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":0.8667936325073242},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.8151358366012573},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.8103824853897095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7079101800918579},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6763268113136292},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.6671078205108643},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6484163403511047},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.595107913017273},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5847054123878479},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5589141249656677},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.46951478719711304},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45212721824645996},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44307368993759155},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.4156859815120697},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.4134637415409088},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32692188024520874},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07273843884468079}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8667936325073242},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.8151358366012573},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8103824853897095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7079101800918579},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6763268113136292},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.6671078205108643},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6484163403511047},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.595107913017273},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5847054123878479},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5589141249656677},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.46951478719711304},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45212721824645996},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44307368993759155},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4156859815120697},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.4134637415409088},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32692188024520874},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07273843884468079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p17-1111","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1111","pdf_url":"https://www.aclweb.org/anthology/P17-1111.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p17-1111","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1111","pdf_url":"https://www.aclweb.org/anthology/P17-1111.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 55th Annual Meeting of the Association for\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2741390671.pdf","grobid_xml":"https://content.openalex.org/works/W2741390671.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W86604388","https://openalex.org/W145476170","https://openalex.org/W1522301498","https://openalex.org/W1598566484","https://openalex.org/W1614298861","https://openalex.org/W1665214252","https://openalex.org/W1860935423","https://openalex.org/W2030904529","https://openalex.org/W2104747875","https://openalex.org/W2110974939","https://openalex.org/W2120661206","https://openalex.org/W2133564696","https://openalex.org/W2134036914","https://openalex.org/W2146502635","https://openalex.org/W2161222299","https://openalex.org/W2172221237","https://openalex.org/W2219792987","https://openalex.org/W2250405765","https://openalex.org/W2250416721","https://openalex.org/W2250451826","https://openalex.org/W2250747734","https://openalex.org/W2250861254","https://openalex.org/W2251811146","https://openalex.org/W2252268838","https://openalex.org/W2296260950","https://openalex.org/W2301095666","https://openalex.org/W2949952998","https://openalex.org/W2950577311","https://openalex.org/W2962934648","https://openalex.org/W2963572611","https://openalex.org/W2964121744","https://openalex.org/W2964310805"],"related_works":["https://openalex.org/W2251084681","https://openalex.org/W2098784136","https://openalex.org/W4241489294","https://openalex.org/W3115565094","https://openalex.org/W287510790","https://openalex.org/W2968543375","https://openalex.org/W4288558800","https://openalex.org/W2953770453","https://openalex.org/W2888625260","https://openalex.org/W2179743027"],"abstract_inverted_index":{"We":[0,98],"present":[1],"neural":[2,20],"network-based":[3],"joint":[4,24,56],"models":[5,16,80,102],"for":[6,22],"Chinese":[7,25,85],"word":[8,40,86],"segmentation,":[9],"POS":[10,89],"tagging":[11],"and":[12,88,91],"dependency":[13,47,96],"parsing.":[14,97],"Our":[15],"are":[17],"the":[18,32,55,59],"first":[19],"approaches":[21],"fully":[23],"analysis":[26],"that":[27,78],"is":[28],"known":[29],"to":[30,54,74],"prevent":[31],"error":[33],"propagation":[34],"problem":[35],"of":[36,69],"pipeline":[37],"models.":[38],"Although":[39],"embeddings":[41,68],"play":[42],"a":[43],"key":[44],"role":[45],"in":[46,58,72,84,95],"parsing,":[48],"they":[49],"cannot":[50],"be":[51],"applied":[52],"directly":[53],"task":[57],"previous":[60],"work.":[61],"To":[62],"address":[63],"this":[64],"problem,":[65],"we":[66],"propose":[67],"character":[70],"strings,":[71],"addition":[73],"words.":[75],"Experiments":[76],"show":[77],"our":[79],"outperform":[81],"existing":[82],"systems":[83],"segmentation":[87],"tagging,":[90],"perform":[92],"preferable":[93],"accuracies":[94],"also":[99],"explore":[100],"bi-LSTM":[101],"with":[103],"fewer":[104],"features.":[105]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
