Triple

T30333168
Position Surface form Disambiguated ID Type / Status
Subject Billy Elliot the Musical (Broadway) E771542 entity
Predicate costumeDesigner P184 FINISHED
Object Nicky Gillibrand
Nicky Gillibrand is a theatre costume designer best known for her work on the stage musical adaptation of "Billy Elliot."
E1912044 NE FINISHED

How this triple was built (2 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: Nicky Gillibrand | Statement: [Billy Elliot the Musical (Broadway), costumeDesigner, Nicky Gillibrand]
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: Nicky Gillibrand
Triple: [Billy Elliot the Musical (Broadway), costumeDesigner, Nicky Gillibrand]
Generated description
Nicky Gillibrand is a theatre costume designer best known for her work on the stage musical adaptation of "Billy Elliot."

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_69f2248aba24819095bb86480d55b23b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f681c9bdf481908f50596dd90053aa completed May 2, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27893352908190bbcf690d684a3d36 completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278a8ff2b88190b11c0d9fa2ce6c76 completed June 9, 2026, 3:37 a.m.
NED2 Entity disambiguation (via description) batch_6a278b1083c081908e01a6fa281800c0 completed June 9, 2026, 3:40 a.m.
Created at: April 29, 2026, 7:53 p.m.