{"id":"https://openalex.org/W7111182683","doi":"https://doi.org/10.1145/3731443.3771362","title":"Improving BPMN Model Generation from Texts through a Prompt-Guided Fusion of NLP and LLM Approaches","display_name":"Improving BPMN Model Generation from Texts through a Prompt-Guided Fusion of NLP and LLM Approaches","publication_year":2025,"publication_date":"2025-12-09","ids":{"openalex":"https://openalex.org/W7111182683","doi":"https://doi.org/10.1145/3731443.3771362"},"language":null,"primary_location":{"id":"doi:10.1145/3731443.3771362","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731443.3771362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Knowledge Capture Conference 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Intissar Boujmil","orcid":"https://orcid.org/0009-0002-6605-8144"},"institutions":[{"id":"https://openalex.org/I8636806","display_name":"University of Sousse","ror":"https://ror.org/00dmpgj58","country_code":"TN","type":"education","lineage":["https://openalex.org/I8636806"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Intissar Boujmil","raw_affiliation_strings":["ISG Sousse, University of Sousse, Department of Management Information Systems, Sousse, Tunisia"],"raw_orcid":"https://orcid.org/0009-0002-6605-8144","affiliations":[{"raw_affiliation_string":"ISG Sousse, University of Sousse, Department of Management Information Systems, Sousse, Tunisia","institution_ids":["https://openalex.org/I8636806"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wiem Chebil","orcid":"https://orcid.org/0000-0003-1491-1246"},"institutions":[{"id":"https://openalex.org/I166928557","display_name":"University of Monastir","ror":"https://ror.org/00nhtcg76","country_code":"TN","type":"education","lineage":["https://openalex.org/I166928557"]},{"id":"https://openalex.org/I83259278","display_name":"Manouba University","ror":"https://ror.org/0503ejf32","country_code":"TN","type":"education","lineage":["https://openalex.org/I83259278"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Wiem Chebil","raw_affiliation_strings":["ENSI, University of Manouba, RIADI Laboratory, Manouba, Tunisia","ISI Mahdia, University of Monastir, Department of Computer Science, Monastir, Tunisia"],"raw_orcid":"https://orcid.org/0000-0003-1491-1246","affiliations":[{"raw_affiliation_string":"ENSI, University of Manouba, RIADI Laboratory, Manouba, Tunisia","institution_ids":["https://openalex.org/I83259278"]},{"raw_affiliation_string":"ISI Mahdia, University of Monastir, Department of Computer Science, Monastir, Tunisia","institution_ids":["https://openalex.org/I166928557"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I8636806"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.77993579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"165","last_page":"169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.44609999656677246,"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":0.44609999656677246,"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":0.12139999866485596,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.041999999433755875,"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/process","display_name":"Process (computing)","score":0.5475000143051147},{"id":"https://openalex.org/keywords/business-process-model-and-notation","display_name":"Business Process Model and Notation","score":0.4860000014305115},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4361000061035156},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3783999979496002},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3659999966621399},{"id":"https://openalex.org/keywords/computational-linguistics","display_name":"Computational linguistics","score":0.31529998779296875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083999752998352},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6359999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6065000295639038},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5475000143051147},{"id":"https://openalex.org/C179299601","wikidata":"https://www.wikidata.org/wiki/Q1017605","display_name":"Business Process Model and Notation","level":5,"score":0.4860000014305115},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.30550000071525574},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.250900000333786},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731443.3771362","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731443.3771362","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Knowledge Capture Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8314214944839478,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W207431025","https://openalex.org/W2099019682","https://openalex.org/W2617290256","https://openalex.org/W2885594628","https://openalex.org/W2930673238","https://openalex.org/W4292155354","https://openalex.org/W4306955967","https://openalex.org/W4390694561","https://openalex.org/W4392781032","https://openalex.org/W4403199294","https://openalex.org/W4403793823","https://openalex.org/W4407553807","https://openalex.org/W4409639706"],"related_works":[],"abstract_inverted_index":{"The":[0,71],"automatic":[1],"generation":[2,143],"of":[3,73,81,94,118,126,144],"BPMN":[4,35,84],"models":[5,36,51,85],"from":[6,86],"textual":[7,87],"descriptions":[8,88],"remains":[9],"a":[10,104,110],"major":[11],"challenge,":[12],"particularly":[13,131],"when":[14],"dealing":[15],"with":[16,28,114],"long":[17],"and":[18,97,128],"complex":[19],"texts.":[20],"Traditional":[21],"natural":[22],"language":[23,50],"processing":[24],"(NLP)":[25],"approaches":[26,96],"struggle":[27],"linguistic":[29],"disambiguation,":[30],"often":[31],"resulting":[32],"in":[33],"incorrect":[34],"characterized":[37],"by":[38,89],"overloaded":[39],"or":[40],"missing":[41],"relevant":[42],"process":[43],"elements.":[44],"On":[45],"the":[46,79,91,115,124,133,142],"other":[47],"hand,":[48],"large":[49],"(LLMs)":[52],"such":[53],"as":[54],"GPT-4,":[55],"while":[56,136],"effective":[57],"at":[58],"capturing":[59],"semantic":[60],"nuances,":[61],"tend":[62],"to":[63,77,141],"omit":[64],"key":[65],"elements":[66],"required":[67],"for":[68,132,147],"complete":[69],"modeling.":[70],"objective":[72],"this":[74,100],"study":[75],"is":[76],"improve":[78],"quality":[80],"automatically":[82],"generated":[83],"overcoming":[90],"respective":[92],"limitations":[93],"traditional":[95],"GPT-4.":[98,119],"To":[99],"end,":[101],"we":[102],"propose":[103],"prompt-guided":[105],"fusion":[106,121],"method":[107],"that":[108],"combines":[109],"literature-based":[111],"NLP":[112,134],"approach":[113],"reasoning":[116],"capabilities":[117],"This":[120],"helps":[122],"reduce":[123],"overload":[125],"activities":[127],"exclusive":[129],"gateways,":[130],"approach,":[135],"partially":[137],"correcting":[138],"errors":[139],"related":[140],"parallel":[145],"gateways":[146],"both":[148],"approaches.":[149]},"counts_by_year":[],"updated_date":"2025-12-10T02:49:46.989445","created_date":"2025-12-10T00:00:00"}