Triple

T24766139
Position Surface form Disambiguated ID Type / Status
Subject Frank Warren E619587 entity
Predicate employer P7 FINISHED
Object Queensberry Promotions
Queensberry Promotions is a British boxing promotion company founded and run by veteran fight promoter Frank Warren, known for staging major professional boxing events in the UK.
E1651370 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: Queensberry Promotions | Statement: [Frank Warren, employer, Queensberry Promotions]
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: Queensberry Promotions
Triple: [Frank Warren, employer, Queensberry Promotions]
Generated description
Queensberry Promotions is a British boxing promotion company founded and run by veteran fight promoter Frank Warren, known for staging major professional boxing events in the UK.

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_69e2fabbea94819092ed41348909622f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410a5e2688190830b6fb4c309f28f completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c14429881908c4008433c8fd7f9 completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a1024aaf1e48190b70f890bfa9a1ec4 completed May 22, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a1025c5fb188190bd117ec73114af3e completed May 22, 2026, 9:45 a.m.
Created at: April 18, 2026, 4:28 a.m.