Triple

T27057253
Position Surface form Disambiguated ID Type / Status
Subject Article XV squadron E684930 entity
Predicate notableExample P1503 FINISHED
Object No. 6 Squadron SAAF
No. 6 Squadron SAAF was a South African Air Force unit formed under the British Commonwealth Air Training Plan during World War II, serving primarily in maritime patrol and coastal defense roles.
 E1755156 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. 6 Squadron SAAF | Statement: [Article XV squadron, notableExample, No. 6 Squadron SAAF]
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. 6 Squadron SAAF
Triple: [Article XV squadron, notableExample, No. 6 Squadron SAAF]
Generated description
No. 6 Squadron SAAF was a South African Air Force unit formed under the British Commonwealth Air Training Plan during World War II, serving primarily in maritime patrol and coastal defense 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_69ef14829fac8190914bef9ecc3005d7 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622b425d48190ae5b1490ebee40f2 completed May 2, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123acea7208190978f664e8000af6c completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123bd93ac081909b060b395b1d3e81 completed May 23, 2026, 11:44 p.m.
NED2 Entity disambiguation (via description) batch_6a123c4f67388190a885b5ce89f9baa6 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 8:18 a.m.