{"id":"https://openalex.org/W7154047779","doi":"https://doi.org/10.48550/arxiv.2604.09470","title":"Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL","display_name":"Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154047779","doi":"https://doi.org/10.48550/arxiv.2604.09470"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09470","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09470","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075151009","display_name":"Vishnu Murali","orcid":"https://orcid.org/0000-0002-8762-5614"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Murali, Vishnu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133506254","display_name":"Anmol Gulati","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gulati, Anmol","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133521836","display_name":"Elias Lumer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lumer, Elias","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133542491","display_name":"Kevin Frank","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frank, Kevin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133520832","display_name":"Sindy Campagna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Campagna, Sindy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133552043","display_name":"Vamse Kumar Subbiah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Subbiah, Vamse Kumar","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5075151009"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.5389999747276306,"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":0.5389999747276306,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.13330000638961792,"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":0.08730000257492065,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7257999777793884},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.72079998254776},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5038999915122986},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47760000824928284},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4293999969959259},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4153999984264374},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.38530001044273376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7258999943733215},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7257999777793884},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.72079998254776},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5038999915122986},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47760000824928284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4699000120162964},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43459999561309814},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4293999969959259},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C77660490","wikidata":"https://www.wikidata.org/wiki/Q244916","display_name":"Intermediate language","level":3,"score":0.359499990940094},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30489999055862427},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.26570001244544983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09470","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09470","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09470","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Translating":[0],"natural":[1,65],"language":[2,66],"into":[3],"Jira":[4,38,86,113],"Query":[5],"Language":[6],"(JQL)":[7],"requires":[8],"resolving":[9],"ambiguous":[10,56],"field":[11],"references,":[12],"instance-specific":[13],"categorical":[14,25,127],"values,":[15],"and":[16,116,206,233],"complex":[17],"Boolean":[18],"predicates.":[19],"Single-pass":[20],"LLMs":[21,106,136],"cannot":[22],"discover":[23],"which":[24],"values":[26,128],"(e.g.,":[27],"component":[28],"names":[29],"or":[30,55],"fix":[31],"versions)":[32],"actually":[33],"exist":[34],"in":[35,175],"a":[36,47,84,101,118,165,176],"given":[37],"instance,":[39],"nor":[40],"can":[41],"they":[42],"verify":[43],"generated":[44],"queries":[45],"against":[46],"live":[48,85,108],"data":[49],"source,":[50],"limiting":[51],"accuracy":[52,144,182,190],"on":[53,83,95,145,169],"paraphrased":[54],"requests.":[57],"No":[58],"open,":[59],"execution-based":[60,75],"benchmark":[61,77],"exists":[62],"for":[63,222],"mapping":[64],"to":[67,186,194,219,236],"JQL.":[68],"We":[69,225],"introduce":[70],"Jackal,":[71,96,100],"the":[72,112,170,210,228],"first":[73],"large-scale,":[74],"text-to-JQL":[76,151],"comprising":[78],"100,000":[79],"validated":[80],"NL-JQL":[81],"pairs":[82],"instance":[87],"with":[88,107,164,188],"over":[89],"200,000":[90],"issues.":[91],"To":[92],"establish":[93],"baselines":[94],"we":[97],"propose":[98],"Agentic":[99],"tool-augmented":[102],"agent":[103,231],"that":[104,122,150],"equips":[105],"query":[109],"execution":[110,143],"via":[111],"MCP":[114],"server":[115],"JiraAnchor,":[117,180],"semantic":[119,200],"retrieval":[120],"tool":[121],"resolves":[123],"natural-language":[124,147],"mentions":[125],"of":[126,161],"through":[129],"embedding-based":[130],"similarity":[131],"search.":[132],"Among":[133],"9":[134,162],"frontier":[135],"evaluated,":[137],"single-pass":[138],"models":[139],"average":[140],"only":[141],"43.4%":[142],"short":[146],"queries,":[148],"highlighting":[149],"remains":[152],"an":[153],"open":[154],"challenge.":[155],"The":[156],"agentic":[157],"approach":[158],"improves":[159],"7":[160],"models,":[163],"9.0%":[166],"relative":[167],"gain":[168],"most":[171],"linguistically":[172],"challenging":[173],"variant;":[174],"controlled":[177],"ablation":[178],"isolating":[179],"categorical-value":[181],"rises":[183],"from":[184,192],"48.7%":[185],"71.7%,":[187],"component-field":[189],"jumping":[191],"16.9%":[193],"66.2%.":[195],"Our":[196],"analysis":[197],"identifies":[198],"inherent":[199],"ambiguities,":[201],"such":[202],"as":[203,209],"issue-type":[204],"disambiguation":[205],"text-field":[207],"selection,":[208],"dominant":[211],"failure":[212],"modes":[213],"rather":[214],"than":[215],"value-resolution":[216],"errors,":[217],"pointing":[218],"concrete":[220],"directions":[221],"future":[223],"work.":[224],"publicly":[226],"release":[227],"benchmark,":[229],"all":[230],"transcripts,":[232],"evaluation":[234],"code":[235],"support":[237],"reproducibility.":[238]},"counts_by_year":[],"updated_date":"2026-04-14T06:08:25.285971","created_date":"2026-04-14T00:00:00"}