Triple
T32988336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HP Vectra |
E844007
|
entity |
| Predicate | includedModelVariants |
P172991
|
FINISHED |
| Object | HP Vectra VL |
E844007
|
NE 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: HP Vectra VL | Statement: [HP Vectra, includedModelVariants, HP Vectra VL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedModelVariants Context triple: [HP Vectra, includedModelVariants, HP Vectra VL]
-
A.
vehicleVariant
chosen
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
-
B.
resultedInVehicleVariant
Indicates that one event, process, or action led to the creation or emergence of a specific variant of a vehicle.
-
C.
hasVariantsIn
Indicates that an entity exists in multiple alternative forms or versions within a specified context or set.
-
D.
includesModelsFrom
Indicates that one collection, set, or group contains models that originate from or are derived from another source or collection.
-
E.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
- F. None of above.
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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a022c5269888190944314074aedfe73 |
completed | May 11, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34dac2ea9481909e110a64206e2b63 |
completed | June 19, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_6a02286020308190b238183f7ba2065f |
completed | May 11, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:22 a.m.