Triple

T26990064
Position Surface form Disambiguated ID Type / Status
Subject SAM 26000 E679840 entity
Predicate registration P3328 FINISHED
Object USAF 62-6000
USAF 62-6000 is a United States Air Force Boeing VC-137C aircraft best known for serving as Air Force One for several U.S. presidents, including John F. Kennedy and Lyndon B. Johnson.
E1751969 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: USAF 62-6000 | Statement: [SAM 26000, registration, USAF 62-6000]
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: USAF 62-6000
Triple: [SAM 26000, registration, USAF 62-6000]
Generated description
USAF 62-6000 is a United States Air Force Boeing VC-137C aircraft best known for serving as Air Force One for several U.S. presidents, including John F. Kennedy and Lyndon B. Johnson.

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_69eeeb5138ac8190b3c273ddc659a54f completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6218eac6c81909b76d7ea67b47e8f completed May 2, 2026, 4:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229b654548190a4713fcd562dac9d completed May 23, 2026, 10:27 p.m.
NEDg Description generation batch_6a122a5774408190b156c205e764e896 completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122b1ce9a48190935b3499f77d0a1e completed May 23, 2026, 10:33 p.m.
Created at: April 27, 2026, 6:51 a.m.