Triple

T33193404
Position Surface form Disambiguated ID Type / Status
Subject Kenny Ball and His Jazzmen E849676 entity
Predicate hasMember P10 FINISHED
Object John Bennett
John Bennett is a British jazz trombonist best known for his long-standing role in Kenny Ball and His Jazzmen, a leading traditional jazz band of the 1960s.
E2048150 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 Bennett | Statement: [Kenny Ball and His Jazzmen, hasMember, John Bennett]
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 Bennett
Triple: [Kenny Ball and His Jazzmen, hasMember, John Bennett]
Generated description
John Bennett is a British jazz trombonist best known for his long-standing role in Kenny Ball and His Jazzmen, a leading traditional jazz band of the 1960s.

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_69f3495e0f108190a6a7006f79f9c2c3 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d9e085a881908f689884877f90f8 completed May 3, 2026, 5:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3551e9b63c81909bfaab3cf1487243 completed June 19, 2026, 2:27 p.m.
NEDg Description generation batch_6a35539cee748190aa3fadd97f5949a5 completed June 19, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_6a355d0f9bf48190bb4e314ec6359308 completed June 19, 2026, 3:15 p.m.
Created at: May 1, 2026, 1:29 a.m.