Triple

T33338581
Position Surface form Disambiguated ID Type / Status
Subject JaQuel Knight E853606 entity
Predicate founded P104 FINISHED
Object JaQuel Knight Foundation
The JaQuel Knight Foundation is a nonprofit organization created by renowned choreographer JaQuel Knight to support and empower dancers and creatives through advocacy, education, and resources.
E2047569 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: JaQuel Knight Foundation | Statement: [JaQuel Knight, founded, JaQuel Knight Foundation]
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: JaQuel Knight Foundation
Triple: [JaQuel Knight, founded, JaQuel Knight Foundation]
Generated description
The JaQuel Knight Foundation is a nonprofit organization created by renowned choreographer JaQuel Knight to support and empower dancers and creatives through advocacy, education, and resources.

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_69f34969614c81909cd99661b0902533 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6df64c3c08190b33aed03e6ffbb36 completed May 3, 2026, 5:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3552019c608190a094ac3c02837b86 completed June 19, 2026, 2:28 p.m.
NEDg Description generation batch_6a3555bf634c8190bf6496f3c19085af completed June 19, 2026, 2:44 p.m.
NED2 Entity disambiguation (via description) batch_6a35562162288190947ce79e2b65963b completed June 19, 2026, 2:45 p.m.
Created at: May 1, 2026, 1:34 a.m.