Triple

T2289823
Position Surface form Disambiguated ID Type / Status
Subject Burlesque E51475 entity
Predicate character P662 FINISHED
Object Nikki
Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
 E252773 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nikki | Statement: [Burlesque, character, Nikki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nikki
Context triple: [Burlesque, character, Nikki]
  • A. Nikkiya
    Nikkiya is an American singer and rapper known for her collaborations in hip-hop and R&B, particularly with producer and artist K.E. on the Track (Keys).
  • B. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • C. Nicky
    Nicky is a diminutive or nickname commonly used for the given name Nicholas.
  • D. Natalie
    Natalie is a fictional character from the romantic comedy universe of "Love Actually," appearing in the charity sequel short film "Red Nose Day Actually."
  • E. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nikki
Triple: [Burlesque, character, Nikki]
Generated description
Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nikki
Target entity description: Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
  • A. Nikkiya
    Nikkiya is an American singer and rapper known for her collaborations in hip-hop and R&B, particularly with producer and artist K.E. on the Track (Keys).
  • B. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • C. Nicky
    Nicky is a diminutive or nickname commonly used for the given name Nicholas.
  • D. Natalie
    Natalie is a fictional character from the romantic comedy universe of "Love Actually," appearing in the charity sequel short film "Red Nose Day Actually."
  • E. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc273b67c8190bcd96f9a484647ef completed March 7, 2026, 6:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f1e84ac819096cb62ce5e94d865 completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae7fee12ac8190bb9924f7467434a6 completed March 9, 2026, 8:08 a.m.
NED2 Entity disambiguation (via description) batch_69ae8061cd348190b0b0b65dcf730f99 completed March 9, 2026, 8:10 a.m.
Created at: March 4, 2026, 7:48 p.m.