Triple

T34033586
Position Surface form Disambiguated ID Type / Status
Subject RAF Hucknall E872725 entity
Predicate hostedUnit P3556 FINISHED
Object No. 3660 Fighter Control Unit
No. 3660 Fighter Control Unit was a Royal Air Force ground-based radar and control unit responsible for directing and coordinating fighter aircraft operations.
E2152513 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: No. 3660 Fighter Control Unit | Statement: [RAF Hucknall, hostedUnit, No. 3660 Fighter Control Unit]
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: No. 3660 Fighter Control Unit
Triple: [RAF Hucknall, hostedUnit, No. 3660 Fighter Control Unit]
Generated description
No. 3660 Fighter Control Unit was a Royal Air Force ground-based radar and control unit responsible for directing and coordinating fighter aircraft operations.

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_69f349a2527c81909a7cd4bda94d70ad completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70b3acdbc8190b90f48e64ad82e74 completed May 3, 2026, 8:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a387cee1af881909ab12d4093114295 completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387da3cca88190871b690e2ee62c9e completed June 22, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a387e3b94cc8190bfc6b69d756793fb completed June 22, 2026, 12:13 a.m.
Created at: May 1, 2026, 1:51 a.m.