Triple

T34033582
Position Surface form Disambiguated ID Type / Status
Subject RAF Hucknall E872725 entity
Predicate hostedUnit P3556 FINISHED
Object No. 3656 Fighter Control Unit
No. 3656 Fighter Control Unit was a Royal Air Force unit responsible for coordinating and directing fighter aircraft operations, particularly in the air defense role.
E2145254 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. 3656 Fighter Control Unit | Statement: [RAF Hucknall, hostedUnit, No. 3656 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. 3656 Fighter Control Unit
Triple: [RAF Hucknall, hostedUnit, No. 3656 Fighter Control Unit]
Generated description
No. 3656 Fighter Control Unit was a Royal Air Force unit responsible for coordinating and directing fighter aircraft operations, particularly in the air defense role.

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_6a3852cbf92881909d6e3ba5e0881e63 completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a38537cefd48190b5d223a5506b4f2d completed June 21, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a38546765988190bba6f0bc046274df completed June 21, 2026, 9:15 p.m.
Created at: May 1, 2026, 1:51 a.m.