Triple

T33641395
Position Surface form Disambiguated ID Type / Status
Subject African Jazz and Variety E861842 entity
Predicate title P38 FINISHED
Object African Jazz and Variety
African Jazz and Variety was a pioneering South African musical revue and touring show that showcased African jazz, dance, and popular entertainment during the apartheid era.
E2062274 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: African Jazz and Variety | Statement: [African Jazz and Variety, title, African Jazz and Variety]
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: African Jazz and Variety
Triple: [African Jazz and Variety, title, African Jazz and Variety]
Generated description
African Jazz and Variety was a pioneering South African musical revue and touring show that showcased African jazz, dance, and popular entertainment during the apartheid era.

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_69f3498280c48190bcc3494017d14234 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f977729081908a25fa155ce135ca completed May 3, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3627184738819084171a3bc1a569c5 completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a36289df2dc8190a6265c22c12f5fef completed June 20, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_6a362919e1b081909e0d3907323d4e9d completed June 20, 2026, 5:46 a.m.
Created at: May 1, 2026, 1:42 a.m.