Triple
T31989715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canik TP9 series |
E816829
|
entity |
| Predicate | hasSubcompactVariant |
P172991
|
FINISHED |
| Object | Canik TP9 Elite SC |
—
|
NE NERFINISHED |
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: Canik TP9 Elite SC | Statement: [Canik TP9 series, hasSubcompactVariant, Canik TP9 Elite SC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubcompactVariant Context triple: [Canik TP9 series, hasSubcompactVariant, Canik TP9 Elite SC]
-
A.
hasHatchback
Indicates that one entity possesses or is characterized by having a hatchback-style vehicle or body type.
-
B.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
-
C.
wheelbaseVariantOf
Indicates a relationship where one vehicle’s wheelbase configuration is a variant or modified version of another vehicle’s wheelbase.
-
D.
vehicleVariant
chosen
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
-
E.
resultedInVehicleVariant
Indicates that one event, process, or action led to the creation or emergence of a specific variant of a vehicle.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: May 1, 2026, 12:13 a.m.