Triple

T32412334
Position Surface form Disambiguated ID Type / Status
Subject No. 457 Squadron RAAF E828257 entity
Predicate airForceNumbering P44071 FINISHED
Object No. 457 Squadron
No. 457 Squadron was a Royal Australian Air Force fighter squadron that served notably in World War II, including in the defense of Australia and operations in the Pacific.
E2008740 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. 457 Squadron | Statement: [No. 457 Squadron RAAF, airForceNumbering, No. 457 Squadron]
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. 457 Squadron
Triple: [No. 457 Squadron RAAF, airForceNumbering, No. 457 Squadron]
Generated description
No. 457 Squadron was a Royal Australian Air Force fighter squadron that served notably in World War II, including in the defense of Australia and operations in the Pacific.

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_69f34919f300819092b541c6277cd68a completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2574a288190b39da76887444b3b completed May 3, 2026, 3:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34666ee9308190b97b7ecddd931a01 completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a3468104f4c8190bfae60a51dee0b35 completed June 18, 2026, 9:50 p.m.
NED2 Entity disambiguation (via description) batch_6a346ae8a91081909a10179607fe69a8 completed June 18, 2026, 10:02 p.m.
Created at: May 1, 2026, 12:53 a.m.