Triple

T35328498
Position Surface form Disambiguated ID Type / Status
Subject Blond Ambition World Tour E1020256 entity
Predicate soundDesigner P32563 FINISHED
Object John Miceli
John Miceli is a professional sound designer and audio engineer best known for his work on major concert tours, including Madonna’s Blond Ambition World Tour.
E2288872 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: John Miceli | Statement: [Blond Ambition World Tour, soundDesigner, John Miceli]
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: John Miceli
Triple: [Blond Ambition World Tour, soundDesigner, John Miceli]
Generated description
John Miceli is a professional sound designer and audio engineer best known for his work on major concert tours, including Madonna’s Blond Ambition World Tour.

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_69f76deacf4481908e7735a5a7715b0a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7910d5bcc819094af3977d4b235a5 completed May 3, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5ae5967d4481908e3dd9e92caa51ca completed July 18, 2026, 2:31 a.m.
NEDg Description generation batch_6a5ae654bec481908efd8c67bf61fa72 completed July 18, 2026, 2:35 a.m.
NED2 Entity disambiguation (via description) batch_6a5ae6fb3220819084e3b2125ce9e453 completed July 18, 2026, 2:37 a.m.
Created at: May 3, 2026, 4:03 p.m.