{"id":"https://openalex.org/W2966469393","doi":"https://doi.org/10.24963/ijcai.2019/691","title":"Modeling Source Syntax and Semantics for Neural AMR Parsing","display_name":"Modeling Source Syntax and Semantics for Neural AMR Parsing","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966469393","doi":"https://doi.org/10.24963/ijcai.2019/691","mag":"2966469393"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/691","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/691","pdf_url":"https://www.ijcai.org/proceedings/2019/0691.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0691.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040635760","display_name":"Donglai Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"DongLai Ge","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369260","display_name":"Junhui Li","orcid":"https://orcid.org/0000-0001-7829-6348"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhui Li","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101923144","display_name":"Muhua Zhu","orcid":"https://orcid.org/0000-0002-6519-2379"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muhua Zhu","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003885809","display_name":"Shoushan Li","orcid":"https://orcid.org/0000-0002-1000-3278"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoushan Li","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4975","last_page":"4981"},"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":0.9894999861717224,"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":0.864245593547821},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.8048765063285828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6966361403465271},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6923401951789856},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6866395473480225},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.6366344094276428},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5265655517578125},{"id":"https://openalex.org/keywords/semantic-role-labeling","display_name":"Semantic role labeling","score":0.4839901924133301},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1648792028427124}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.864245593547821},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.8048765063285828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6966361403465271},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6923401951789856},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6866395473480225},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.6366344094276428},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5265655517578125},{"id":"https://openalex.org/C67277372","wikidata":"https://www.wikidata.org/wiki/Q7449085","display_name":"Semantic role labeling","level":3,"score":0.4839901924133301},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1648792028427124}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/691","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/691","pdf_url":"https://www.ijcai.org/proceedings/2019/0691.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/691","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/691","pdf_url":"https://www.ijcai.org/proceedings/2019/0691.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3821383714","display_name":null,"funder_award_id":"61751206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5678221373","display_name":null,"funder_award_id":"61876120","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966469393.pdf","grobid_xml":"https://content.openalex.org/works/W2966469393.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W222053410","https://openalex.org/W1522301498","https://openalex.org/W1869752048","https://openalex.org/W2149837184","https://openalex.org/W2250375035","https://openalex.org/W2250623140","https://openalex.org/W2251171690","https://openalex.org/W2251823395","https://openalex.org/W2251943262","https://openalex.org/W2296308987","https://openalex.org/W2563574619","https://openalex.org/W2740241688","https://openalex.org/W2752593721","https://openalex.org/W2788802500","https://openalex.org/W2793978524","https://openalex.org/W2799190973","https://openalex.org/W2890212927","https://openalex.org/W2962784628","https://openalex.org/W2962947230","https://openalex.org/W2963069010","https://openalex.org/W2963161698","https://openalex.org/W2963691697","https://openalex.org/W2963720566","https://openalex.org/W2963913268","https://openalex.org/W2963925437","https://openalex.org/W2964116568","https://openalex.org/W2964121744","https://openalex.org/W2964164798","https://openalex.org/W2964253663","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2077104824","https://openalex.org/W2168778844","https://openalex.org/W4391150403","https://openalex.org/W2081749821","https://openalex.org/W1968572830","https://openalex.org/W2921384283","https://openalex.org/W2090814745","https://openalex.org/W2029896371","https://openalex.org/W2136497797","https://openalex.org/W2890176538"],"abstract_inverted_index":{"Sequence-to-sequence":[0],"(seq2seq)":[1],"approaches":[2,52,123],"formalize":[3],"Abstract":[4],"Meaning":[5],"Representation":[6],"(AMR)":[7],"parsing":[8],"as":[9,30],"a":[10,14,18,27,31,75,92,100,134],"translation":[11],"task":[12],"from":[13],"source":[15,28,56,69],"sentence":[16,29],"to":[17,53,103],"target":[19],"AMR":[20,63],"graph.":[21],"However,":[22],"previous":[23],"studies":[24],"generally":[25],"model":[26,102],"word":[32],"sequence":[33,77],"but":[34],"ignore":[35],"the":[36,43,87],"inherent":[37],"syntactic":[38,70,80,93,106],"and":[39,58,71,82,94,107,129],"semantic":[40,72,83,95,108],"information":[41],"in":[42,86],"sentence.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48,90],"propose":[49,91],"two":[50,122],"effective":[51],"explicitly":[54,104],"modeling":[55],"syntax":[57],"semantics":[59],"into":[60,74],"neural":[61],"seq2seq":[62,136],"parsing.":[64],"The":[65],"first":[66],"approach":[67,89],"linearizes":[68],"structure":[73],"mixed":[76],"of":[78,127],"words,":[79],"labels,":[81,84],"while":[85],"second":[88],"structure-aware":[96],"encoding":[97],"scheme":[98],"through":[99],"self-attentive":[101],"capture":[105],"relations":[109],"between":[110],"words.":[111],"Experimental":[112],"results":[113],"on":[114],"an":[115],"English":[116],"benchmark":[117],"dataset":[118],"show":[119],"that":[120],"our":[121],"achieve":[124],"significant":[125],"improvement":[126],"3.1%":[128],"3.4%":[130],"F1":[131],"scores":[132],"over":[133],"strong":[135],"baseline.":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}