Triple

T30810149
Position Surface form Disambiguated ID Type / Status
Subject RAF Middle Wallop E784621 entity
Predicate hostedUnit P3556 FINISHED
Object No. 245 Squadron RAF
No. 245 Squadron RAF was a Royal Air Force fighter unit that served with distinction during the Second World War, notably flying Hurricanes and later Typhoons in air defence and ground-attack roles.
 E2283510 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. 245 Squadron RAF | Statement: [RAF Middle Wallop, hostedUnit, No. 245 Squadron RAF]
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. 245 Squadron RAF
Triple: [RAF Middle Wallop, hostedUnit, No. 245 Squadron RAF]
Generated description
No. 245 Squadron RAF was a Royal Air Force fighter unit that served with distinction during the Second World War, notably flying Hurricanes and later Typhoons in air defence and ground-attack roles.

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_69f224b4eda48190bd212ce4f3901e56 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69063edbc81909e7735954aabee0b completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4256c90e9c8190bdce654f13091b85 completed June 29, 2026, 11:28 a.m.
NEDg Description generation batch_6a425a951850819089c343faa55c5799 completed June 29, 2026, 11:44 a.m.
NED2 Entity disambiguation (via description) batch_6a425be74d308190819835b01b6bcc82 completed June 29, 2026, 11:49 a.m.
Created at: April 29, 2026, 8:43 p.m.