Triple

T33731248
Position Surface form Disambiguated ID Type / Status
Subject The Armorer E864280 entity
Predicate stuntDouble P40736 FINISHED
Object Lauren Mary Kim
Lauren Mary Kim is a professional stunt performer and martial artist known for her work doubling prominent characters in film and television, including in the Star Wars franchise.
 E2069478 NE FINISHED

How this triple was built (3 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: Lauren Mary Kim | Statement: [The Armorer, stuntDouble, Lauren Mary Kim]
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: Lauren Mary Kim
Triple: [The Armorer, stuntDouble, Lauren Mary Kim]
Generated description
Lauren Mary Kim is a professional stunt performer and martial artist known for her work doubling prominent characters in film and television, including in the Star Wars franchise.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: stuntDouble
Context triple: [The Armorer, stuntDouble, Lauren Mary Kim]
  • A. hasStuntDouble chosen
    Indicates that one entity serves as a stunt double who performs dangerous or physically demanding actions on behalf of another entity.
  • B. stuntPerformerIn
    Indicates that one entity serves as a stunt performer in a work, production, or performance associated with another entity.
  • C. actsInSteadOf
    Indicates that one entity performs an action or fulfills a role as a substitute or proxy for another entity.
  • D. hasDubActor
    Indicates that one entity serves as the dubbing voice actor for another entity in a particular work or version.
  • E. stuntCoordinatorOn
    Indicates that one entity serves as the stunt coordinator responsible for designing and overseeing stunts on a particular production or project involving another entity.
  • F. None of above.

Provenance (6 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_69f3498a64cc8190b4b414c67b280d93 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fb1eeb64819083f6f04633b000f2 completed May 3, 2026, 7:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366e844f6c819098552979bd6db6b4 completed June 20, 2026, 10:42 a.m.
NEDg Description generation batch_6a366f2eab708190a7ab0579a49a7627 completed June 20, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_6a3670cc13ec8190975f7d3bc74eb00f completed June 20, 2026, 10:51 a.m.
PD Predicate disambiguation batch_69f6f96dd4c8819093d6a7bd046a9ad5 completed May 3, 2026, 7:29 a.m.
Created at: May 1, 2026, 1:44 a.m.