Triple

T29284290

Position	Surface form	Disambiguated ID	Type / Status
Subject	Tiler Peck	`E742465`	entity
Predicate	trainedAt	`P2858`	FINISHED
Object	Westside School of Ballet Westside School of Ballet is a renowned ballet training institution in California known for producing accomplished dancers, including New York City Ballet principal Tiler Peck.	`E1861210`	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: Westside School of Ballet | Statement: [Tiler Peck, trainedAt, Westside School of Ballet]

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: Westside School of Ballet
Triple: [Tiler Peck, trainedAt, Westside School of Ballet]

Generated description

Westside School of Ballet is a renowned ballet training institution in California known for producing accomplished dancers, including New York City Ballet principal Tiler Peck.

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_69f09121ed8c8190b4cb27be3619c262`	completed	April 28, 2026, 10:51 a.m.
NER	Named-entity recognition	`batch_69f665191d888190b4ab2c4bbd7725cb`	completed	May 2, 2026, 8:56 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a25a856fa208190a0141fbccbe92c46`	completed	June 7, 2026, 5:20 p.m.
NEDg	Description generation	`batch_6a25ac72cc788190bd95421cb6bf4897`	completed	June 7, 2026, 5:37 p.m.
NED2	Entity disambiguation (via description)	`batch_6a25b14c4f088190afc5aa0e3d78ab43`	completed	June 7, 2026, 5:58 p.m.

Created at: April 28, 2026, 12:56 p.m.