Triple
T16389923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K200 armored personnel carrier |
E398021
|
entity |
| Predicate | hasRearRamp |
P119068
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [K200 armored personnel carrier, hasRearRamp, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRearRamp Context triple: [K200 armored personnel carrier, hasRearRamp, true]
-
A.
hasVehicleLoadingRamps
Indicates that something is equipped with ramps specifically intended for loading or unloading vehicles.
-
B.
hasRearHingedDoors
Indicates that the subject is equipped with doors whose hinges are located at the rear edge rather than the front.
-
C.
hasRampSpace
Indicates that a location or structure includes designated space for a ramp, allowing sloped access between different levels.
-
D.
containsRamps
chosen
Indicates that one entity includes or is equipped with one or more ramps as part of its structure or features.
-
E.
hasRearUnitType
Indicates that an entity’s rear section or back part is of a specified type.
- F. None of above.
Provenance (3 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e326414f44819093ebc11f1b63444c |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.