Triple
T35614572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VC-137C |
E1029129
|
entity |
| Predicate | airframeSAM27000 |
P184061
|
FINISHED |
| Object | second VC-137C built |
—
|
LITERAL 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: second VC-137C built | Statement: [VC-137C, airframeSAM27000, second VC-137C built]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airframeSAM27000 Context triple: [VC-137C, airframeSAM27000, second VC-137C built]
-
A.
airframeSAM26000
Indicates that an entity serves as or is associated with the specific airframe designated SAM 26000 (the U.S. presidential aircraft).
-
B.
airframe
Indicates that an entity is the structural framework or body of an aircraft associated with another entity (such as a specific model, component, or system).
-
C.
airframeDerivedFrom
Indicates that one airframe design is derived or developed from another pre-existing airframe design.
-
D.
airframeNumber
Indicates the unique identifying number assigned to a specific aircraft’s structural frame within a fleet or system.
-
E.
airframeConstruction
Indicates the method or structural approach used to build an aircraft’s main body and supporting framework.
- F. None of above. chosen
Provenance (4 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:05 p.m.