Triple
T24758732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Havilland Canada CC-115 Buffalo |
E619366
|
entity |
| Predicate | hasCargoRamp |
P64257
|
FINISHED |
| Object | rear loading ramp |
—
|
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: rear loading ramp | Statement: [de Havilland Canada CC-115 Buffalo, hasCargoRamp, rear loading ramp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCargoRamp Context triple: [de Havilland Canada CC-115 Buffalo, hasCargoRamp, rear loading ramp]
-
A.
hasCargoAccess
Indicates that an entity has the ability or permission to access a designated cargo area or its contents.
-
B.
hasCargoDoorVariant
Indicates that one entity is a specific cargo-door-equipped version or configuration variant of another entity.
-
C.
hasCargoHold
Indicates that something possesses a dedicated space or compartment for storing or transporting cargo.
-
D.
hasVehicleLoadingRamps
chosen
Indicates that something is equipped with ramps specifically intended for loading or unloading vehicles.
-
E.
landingGear
Indicates that an entity’s landing gear is present, deployed, or otherwise involved in a landing-related state or action relative to another entity or context.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:26 a.m.