{"id":"https://openalex.org/W7155523527","doi":"https://doi.org/10.48550/arxiv.2604.21782","title":"SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning","display_name":"SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7155523527","doi":"https://doi.org/10.48550/arxiv.2604.21782"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.21782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21782","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":null,"license_id":null,"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.2604.21782","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089338614","display_name":"Hans Ole Hatzel","orcid":"https://orcid.org/0000-0002-4586-7260"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hatzel, Hans Ole","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134494514","display_name":"Ekaterina Artemova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Artemova, Ekaterina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134527091","display_name":"Haimo Paul Stiemer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stiemer, Haimo Paul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134487437","display_name":"Evelyn Gius","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gius, Evelyn","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134498512","display_name":"Chris Biemann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Biemann, Chris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"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/T10028","display_name":"Topic Modeling","score":0.3391999900341034,"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":0.3391999900341034,"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":0.21529999375343323,"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"}},{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.07970000058412552,"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/narrative","display_name":"Narrative","score":0.8251000046730042},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6837000250816345},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.652999997138977},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6013000011444092},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5274999737739563},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.45899999141693115}],"concepts":[{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.8251000046730042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6870999932289124},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6837000250816345},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.652999997138977},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6270999908447266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6071000099182129},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6013000011444092},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5274999737739563},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.45899999141693115},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3779999911785126},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3734000027179718},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3327000141143799},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C78015137","wikidata":"https://www.wikidata.org/wiki/Q847829","display_name":"Narrative structure","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.21782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21782","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.21782","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.21782","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":null,"license_id":null,"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":{"We":[0,38,69,120],"present":[1],"the":[2,56,98,104,112,116,146,151],"shared":[3],"task":[4,17,185],"on":[5,55,159,165],"narrative":[6,9,19,44,49,66],"similarity":[7,20,57],"and":[8,51,100,115,157],"representation":[10],"learning":[11],"-":[12],"NSNRL":[13],"(pronounced":[14],"\"nass-na-rel\").":[15],"The":[16,184],"operationalizes":[18],"as":[21],"a":[22,40,122],"binary":[23],"classification":[24,138,193],"problem:":[25],"determining":[26],"which":[27],"of":[28,43,111,124,145,178,189],"two":[29,73,91,133],"stories":[30],"is":[31],"more":[32,77],"similar":[33],"to":[34],"an":[35,109],"anchor":[36],"story.":[37],"introduce":[39],"novel":[41],"definition":[42],"similarity,":[45],"compatible":[46],"with":[47,83,155,167],"both":[48,182],"theory":[50],"intuitive":[52],"judgment.":[53],"Based":[54],"judgments":[58],"collected":[59,70],"under":[60],"this":[61],"concept,":[62],"we":[63,107],"also":[64],"evaluate":[65],"embedding":[67,152,161],"representations.":[68],"at":[71,89],"least":[72,90],"annotations":[74],"each":[75,84],"for":[76,103,176,195],"than":[78],"1,000":[79],"story":[80],"summary":[81],"triples,":[82],"annotation":[85,101],"being":[86],"backed":[87],"by":[88],"annotators":[92],"in":[93,150,181],"agreement.":[94],"This":[95],"paper":[96],"describes":[97],"sampling":[99],"process":[102],"dataset;":[105],"further,":[106],"give":[108],"overview":[110],"submitted":[113],"systems":[114,154,180],"techniques":[117],"they":[118],"employ.":[119],"received":[121],"total":[123],"71":[125],"final":[126],"submissions":[127],"from":[128],"46":[129],"teams":[130],"across":[131],"our":[132,136],"tracks.":[134,183],"In":[135],"triple-based":[137],"setup,":[139,153],"LLM":[140],"ensembles":[141],"make":[142],"up":[143],"many":[144],"top-scoring":[147],"systems,":[148],"while":[149],"pre-":[156],"post-processing":[158],"pretrained":[160],"models":[162],"perform":[163],"about":[164],"par":[166],"custom":[168],"fine-tuned":[169],"solutions.":[170],"Our":[171],"analysis":[172],"identifies":[173],"potential":[174],"headroom":[175],"improvement":[177],"automated":[179],"website":[186],"includes":[187],"visualizations":[188],"embeddings":[190],"alongside":[191],"instance-level":[192],"results":[194],"all":[196],"teams.":[197]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-25T00:00:00"}
