Triple
T27068422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mazda Kabura |
E685242
|
entity |
| Predicate | driverSideDoorType |
P8655
|
FINISHED |
| Object | conventional front-hinged door |
—
|
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: conventional front-hinged door | Statement: [Mazda Kabura, driverSideDoorType, conventional front-hinged door]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driverSideDoorType Context triple: [Mazda Kabura, driverSideDoorType, conventional front-hinged door]
-
A.
vehicleDoorType
Indicates the specific style or configuration of doors that a vehicle has.
-
B.
hasDoorSide
Indicates that one entity represents a specific side or face of a door in relation to another entity.
-
C.
hasDoor
Indicates that one entity possesses or is equipped with a door that provides access to or through it.
-
D.
hasCargoDoorVariant
Indicates that one entity is a specific cargo-door-equipped version or configuration variant of another entity.
-
E.
doorType
chosen
Indicates the specific kind or category of door associated with an entity.
- 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_69ef14835fcc81908bd737b4267ae528 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 8:26 a.m.