{"id":"https://openalex.org/W7203589816","doi":"https://doi.org/10.70891/tml.2025.060059","title":"A Span-Constrained Decoding Method for Relation Extraction","display_name":"A Span-Constrained Decoding Method for Relation Extraction","publication_year":2025,"publication_date":"2025-10-15","ids":{"openalex":"https://openalex.org/W7203589816","doi":"https://doi.org/10.70891/tml.2025.060059"},"language":"en","primary_location":{"id":"doi:10.70891/tml.2025.060059","doi":"https://doi.org/10.70891/tml.2025.060059","is_oa":true,"landing_page_url":"https://doi.org/10.70891/tml.2025.060059","pdf_url":"https://sub.ifspress.hk/TML/article/download/207/170","source":{"id":"https://openalex.org/S5407049200","display_name":"IFS/ACM Transactions on Machine Learning","issn_l":"3078-5510","issn":["3078-5510"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IFS/ACM Transactions on Machine Learning","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://sub.ifspress.hk/TML/article/download/207/170","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147303863","display_name":"Rui Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Chen","raw_affiliation_strings":["Shenyang Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Normal University","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455138","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-5317-7227","observed_orcids":["https://orcid.org/0000-0002-5317-7227"]},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":["Shenyang Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Normal University","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075917385","display_name":"Chu Zhao","orcid":"https://orcid.org/0000-0002-5649-1545","observed_orcids":["https://orcid.org/0000-0002-5649-1545"]},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chu Zhao","raw_affiliation_strings":["Shenyang Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Normal University","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041576447","display_name":"Shoulin Yin","orcid":"https://orcid.org/0000-0002-5367-1372","observed_orcids":["https://orcid.org/0000-0002-5367-1372"]},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoulin Yin","raw_affiliation_strings":["Shenyang Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Normal University","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077907139","display_name":"Asif Ali Laghari","orcid":"https://orcid.org/0000-0001-5831-5943","observed_orcids":["https://orcid.org/0000-0001-5831-5943"]},"institutions":[{"id":"https://openalex.org/I1281802846","display_name":"Sindh Madressatul Islam University","ror":"https://ror.org/00467a196","country_code":"PK","type":"education","lineage":["https://openalex.org/I1281802846"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Asif Ali Laghari","raw_affiliation_strings":["Sindh Madressatul Islam University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sindh Madressatul Islam University","institution_ids":["https://openalex.org/I1281802846"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2446,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50069465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"2","issue":"1","first_page":"16","last_page":"29"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9785000085830688,"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":0.9785000085830688,"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":0.01510000042617321,"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":0.0017999999690800905,"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/relation-extraction","display_name":"relation extraction","score":0.9850000143051147},{"id":"https://openalex.org/keywords/candidate-filtering","display_name":"candidate filtering","score":0.628000020980835},{"id":"https://openalex.org/keywords/knowledge-modeling","display_name":"knowledge modeling","score":0.3959999978542328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705000042915344},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7253000140190125},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6391000151634216},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5142999887466431},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4672999978065491},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4300000071525574},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3677999973297119},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2572999894618988},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.70891/tml.2025.060059","doi":"https://doi.org/10.70891/tml.2025.060059","is_oa":true,"landing_page_url":"https://doi.org/10.70891/tml.2025.060059","pdf_url":"https://sub.ifspress.hk/TML/article/download/207/170","source":{"id":"https://openalex.org/S5407049200","display_name":"IFS/ACM Transactions on Machine Learning","issn_l":"3078-5510","issn":["3078-5510"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IFS/ACM Transactions on Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.70891/tml.2025.060059","doi":"https://doi.org/10.70891/tml.2025.060059","is_oa":true,"landing_page_url":"https://doi.org/10.70891/tml.2025.060059","pdf_url":"https://sub.ifspress.hk/TML/article/download/207/170","source":{"id":"https://openalex.org/S5407049200","display_name":"IFS/ACM Transactions on Machine Learning","issn_l":"3078-5510","issn":["3078-5510"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IFS/ACM Transactions on Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7567999958992004,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7203589816.pdf","grobid_xml":"https://content.openalex.org/works/W7203589816.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4400910169","https://openalex.org/W4319333278","https://openalex.org/W4401539808","https://openalex.org/W4400643612","https://openalex.org/W2949204161","https://openalex.org/W2994001811","https://openalex.org/W3094235973","https://openalex.org/W7140074262","https://openalex.org/W4415190083","https://openalex.org/W4381744151"],"abstract_inverted_index":{"Driven":[0],"by":[1,130],"the":[2,22,53,62,72,80,108,111,122,151,170,180,192],"accelerating":[3],"digitalization":[4],"of":[5,24,30,57,74,82,127,172],"education,":[6],"artificial":[7],"intelligence":[8],"technologies":[9],"have":[10],"been":[11],"progressively":[12],"embedded":[13],"into":[14],"critical":[15],"application":[16],"scenarios,":[17],"including":[18],"experimental":[19,36,104,188],"pedagogy":[20],"and":[21,32,45,55,79,124,184,202,210],"development":[23],"educational":[25],"resources.":[26],"The":[27,187],"automated":[28],"extraction":[29,67,98,208],"entities":[31],"relations":[33],"from":[34,85],"unstructured":[35],"texts":[37],"constitutes":[38],"a":[39,92,115,131,144,160,165],"foundational":[40],"prerequisite":[41],"for":[42,96,150],"knowledge":[43],"modeling":[44],"semantic":[46],"comprehension,":[47],"with":[48,164],"its":[49],"performance":[50,212],"directly":[51],"governing":[52],"usability":[54],"robustness":[56],"downstream":[58],"systems.":[59],"To":[60],"tackle":[61],"challenges":[63],"confronting":[64],"existing":[65],"relation":[66,97],"methods":[68],"in":[69,107,207],"this":[70],"domain\u2014specifically,":[71],"difficulty":[73],"precisely":[75],"identifying":[76],"entity":[77,136],"boundaries":[78,126],"compounding":[81],"errors":[83],"stemming":[84],"erroneous":[86],"candidate":[87,145],"propagation\u2014this":[88],"paper":[89],"proposes":[90],"SCOPE-CasRel,":[91],"span-constrained":[93,116],"decoding":[94,152],"approach":[95],"specifically":[99],"tailored":[100],"to":[101,134],"secondary":[102],"school":[103],"texts.":[105],"Grounded":[106],"CasRel":[109],"framework,":[110],"proposed":[112,193],"method":[113,194],"introduces":[114],"pairing":[117],"mechanism":[118],"that":[119,191],"jointly":[120],"models":[121],"start":[123],"end":[125],"entities,":[128],"complemented":[129],"length-constrained":[132],"strategy":[133,147],"refine":[135],"span":[137],"selection,":[138],"thereby":[139],"enhancing":[140],"boundary":[141],"consistency.":[142],"Additionally,":[143],"filtering":[146],"is":[148,177],"devised":[149],"phase,":[153],"wherein":[154],"low-confidence":[155],"candidates":[156],"are":[157],"pruned":[158],"via":[159],"dynamic":[161],"threshold":[162],"coupled":[163],"Top-K":[166],"mechanism,":[167],"effectively":[168],"mitigating":[169],"accumulation":[171],"false":[173],"positives.":[174],"Empirical":[175],"validation":[176],"performed":[178],"on":[179],"publicly":[181],"available":[182],"NYT":[183],"WebNLG":[185],"datasets.":[186],"results":[189],"reveal":[190],"surpasses":[195],"several":[196],"mainstream":[197],"baselines":[198],"across":[199],"precision,":[200],"recall,":[201],"F1-score,":[203],"achieving":[204],"substantial":[205],"gains":[206],"accuracy":[209],"overall":[211],"while":[213],"preserving":[214],"strong":[215],"recall":[216],"capability.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-08-17T00:00:00"}