{"id":"https://openalex.org/W7214229174","doi":"https://doi.org/10.18653/2026.oracle-main.31","title":"Recognized but Not Produced: A Generation Benchmark for Culturally Specific Kinship Terms","display_name":"Recognized but Not Produced: A Generation Benchmark for Culturally Specific Kinship Terms","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7214229174","doi":"https://doi.org/10.18653/2026.oracle-main.31"},"language":"en","primary_location":{"id":"doi:10.18653/2026.oracle-main.31","doi":"https://doi.org/10.18653/2026.oracle-main.31","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.oracle-main.31","pdf_url":"https://aclanthology.org/2026.oracle-main.31.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Proceedings of the Workshop on Open Reasoning Across Cultures Languages (ORACLE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.oracle-main.31.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116572277","display_name":"Sahil Pardasani","orcid":"https://orcid.org/0000-0003-2497-8970","observed_orcids":["https://orcid.org/0000-0003-2497-8970"]},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sahil Pardasani","raw_affiliation_strings":["Blockchain Data Intelligence Lab The Pennsylvania State University University Park , PA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Blockchain Data Intelligence Lab The Pennsylvania State University University Park , PA , USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5152769264","display_name":"Madhusudan Singh","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Madhusudan Singh","raw_affiliation_strings":["Blockchain Data Intelligence Lab The Pennsylvania State University University Park , PA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Blockchain Data Intelligence Lab The Pennsylvania State University University Park , PA , USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.63894677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"459","last_page":"467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.6416000127792358,"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":0.6416000127792358,"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":0.29789999127388,"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/T12694","display_name":"Categorization, perception, and language","score":0.02250000089406967,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kinship-terminology","display_name":"kinship terms","score":0.9480000138282776},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.6740000247955322},{"id":"https://openalex.org/keywords/multilingual-language-models","display_name":"multilingual language models","score":0.515999972820282},{"id":"https://openalex.org/keywords/hindi","display_name":"Hindi","score":0.4519999921321869},{"id":"https://openalex.org/keywords/tamil","display_name":"Tamil language","score":0.9959999918937683},{"id":"https://openalex.org/keywords/korean-language","display_name":"Korean language","score":0.9959999918937683},{"id":"https://openalex.org/keywords/paternal-lineages","display_name":"paternal lineages","score":0.42399999499320984},{"id":"https://openalex.org/keywords/vocabulary-knowledge","display_name":"vocabulary knowledge","score":0.49799999594688416},{"id":"https://openalex.org/keywords/llm-benchmarking","display_name":"LLM benchmarking","score":0.4909999966621399}],"concepts":[{"id":"https://openalex.org/C144348335","wikidata":"https://www.wikidata.org/wiki/Q171318","display_name":"Kinship","level":2,"score":0.875},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5340999960899353},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5091999769210815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5020999908447266},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.47940000891685486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46869999170303345},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4487999975681305},{"id":"https://openalex.org/C519982507","wikidata":"https://www.wikidata.org/wiki/Q1568","display_name":"Hindi","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.388700008392334},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C126706616","wikidata":"https://www.wikidata.org/wiki/Q2944660","display_name":"Lexical item","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C2779804580","wikidata":"https://www.wikidata.org/wiki/Q102047","display_name":"Suffix","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C2777062324","wikidata":"https://www.wikidata.org/wiki/Q25036211","display_name":"Preference relation","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C75795011","wikidata":"https://www.wikidata.org/wiki/Q917904","display_name":"Typology","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.2741999924182892},{"id":"https://openalex.org/C2780922921","wikidata":"https://www.wikidata.org/wiki/Q255189","display_name":"Paraphrase","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.2529999911785126}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.oracle-main.31","doi":"https://doi.org/10.18653/2026.oracle-main.31","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.oracle-main.31","pdf_url":"https://aclanthology.org/2026.oracle-main.31.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Proceedings of the Workshop on Open Reasoning Across Cultures Languages (ORACLE)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2609.26942","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.26942","pdf_url":"https://arxiv.org/pdf/2609.26942","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.26942","doi":"https://doi.org/10.48550/arxiv.2609.26942","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.26942","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/2026.oracle-main.31","doi":"https://doi.org/10.18653/2026.oracle-main.31","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.oracle-main.31","pdf_url":"https://aclanthology.org/2026.oracle-main.31.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Proceedings of the Workshop on Open Reasoning Across Cultures Languages (ORACLE)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214229174.pdf","grobid_xml":"https://content.openalex.org/works/W7214229174.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W4404782115","https://openalex.org/W7075994024","https://openalex.org/W7130402983","https://openalex.org/W7162643626","https://openalex.org/W7166844191"],"related_works":["https://openalex.org/W7123585532","https://openalex.org/W7215105706","https://openalex.org/W7101470793","https://openalex.org/W2774629651","https://openalex.org/W7166879185","https://openalex.org/W7220439604","https://openalex.org/W4392088193","https://openalex.org/W7127268979","https://openalex.org/W7135038201","https://openalex.org/W7166854363"],"abstract_inverted_index":{"Current":[0],"literature":[1],"evaluates":[2],"large":[3,133],"language":[4],"models":[5],"(LLMs)":[6],"on":[7],"multilingual":[8],"kinship":[9,27,157],"understanding":[10],"using":[11],"multiple-choice":[12,173],"benchmarks,":[13],"treating":[14],"it":[15,131],"as":[16,99],"a":[17,45,147],"recognition":[18],"problem.We":[19],"instead":[20],"prompt":[21],"five":[22],"open-weight":[23],"LLMs":[24],"to":[25,123],"generate":[26],"terms":[28,88],"in":[29,58,69,134,140],"three":[30],"non-Western":[31],"languages":[32],"(Hindi,":[33],"Tamil,":[34],"and":[35,41,89,168],"Korean)":[36],"across":[37],"two":[38],"communicative":[39],"tasks,":[40],"pair":[42],"this":[43],"with":[44],"matched":[46],"option-supported":[47],"selection":[48],"baseline.On":[49],"identical":[50],"relation-language":[51],"cells,":[52],"GPT-OSS-120B":[53],"selects":[54],"the":[55,72,76,82,86,95,163],"correct":[56],"term":[57,68],"90.67%":[59],"of":[60,71],"75":[61],"valid":[62],"cells":[63],"but":[64,136],"produces":[65],"an":[66,100],"accepted":[67],"36.00%":[70],"corresponding":[73],"attempts;":[74],"Llama-3.3-70Bshows":[75],"same":[77],"pattern":[78],"(77.92%":[79],"versus":[80],"24.24%).Since":[81],"four-option":[83],"condition":[84],"displays":[85],"candidate":[87],"does":[90],"not":[91],"require":[92],"script":[93],"production,":[94],"difference":[96],"is":[97,110,129,132,165],"interpreted":[98],"evaluation-format":[101],"gap":[102],"rather":[103],"than":[104],"direct":[105],"proof":[106],"that":[107,154],"lexical":[108],"knowledge":[109],"intact.On":[111],"explicitly":[112,166],"specified":[113],"L3":[114],"prompts,":[115],"accuracy":[116],"varies":[117],"sharply,":[118],"from":[119],"GLM-5.1":[120],"at":[121,125],"72.29%":[122],"Llama-3.3-70B":[124],"24.24%.The":[126],"paternal-lineage":[127],"advantage":[128],"language-specific:":[130],"Hindi,":[135],"weak":[137],"or":[138],"reversed":[139],"Korean,":[141],"while":[142],"Tamil":[143],"shared-term":[144],"pairs":[145],"provide":[146],"control":[148],"for":[149],"measurement":[150],"variation.These":[151],"results":[152],"show":[153],"culturally":[155],"specific":[156],"generation":[158],"remains":[159],"difficult":[160],"even":[161],"when":[162],"relationship":[164],"stated":[167],"motivate":[169],"generation-based":[170],"evaluation":[171],"alongside":[172],"testing.":[174]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-09-25T00:00:00"}