Triple

T33798562
Position Surface form Disambiguated ID Type / Status
Subject BBC Jazz Awards Lifetime Achievement Award E866142 entity
Predicate hasRecipient P108 FINISHED
Object John Taylor
John Taylor was a highly respected British jazz pianist and composer renowned for his lyrical style and influential contributions to European jazz.
E2067796 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 Taylor | Statement: [BBC Jazz Awards Lifetime Achievement Award, hasRecipient, John Taylor]
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 Taylor
Triple: [BBC Jazz Awards Lifetime Achievement Award, hasRecipient, John Taylor]
Generated description
John Taylor was a highly respected British jazz pianist and composer renowned for his lyrical style and influential contributions to European jazz.

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_69f3498f99f481909cb271f4965a7594 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6ff494d5081908582e516ccf03932 completed May 3, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366595c6e4819090c998764d9b66e9 completed June 20, 2026, 10:04 a.m.
NEDg Description generation batch_6a366681d7b081909116d5a094c1e407 completed June 20, 2026, 10:08 a.m.
NED2 Entity disambiguation (via description) batch_6a3666ebe7ec8190a279f7eb183cf157 completed June 20, 2026, 10:09 a.m.
Created at: May 1, 2026, 1:46 a.m.