Triple
T21177173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelso Dunes Road |
E521842
|
entity |
| Predicate | typicalVehicleRecommendation |
P82336
|
FINISHED |
| Object | high-clearance vehicle recommended |
—
|
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: high-clearance vehicle recommended | Statement: [Kelso Dunes Road, typicalVehicleRecommendation, high-clearance vehicle recommended]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVehicleRecommendation Context triple: [Kelso Dunes Road, typicalVehicleRecommendation, high-clearance vehicle recommended]
-
A.
recommendedVehicle
chosen
Indicates that one entity suggests or endorses a particular vehicle as suitable or preferable for another entity or purpose.
-
B.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
C.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
-
D.
vehicleStandard
Indicates that something complies with, or is defined according to, a specified vehicle-related standard or regulatory specification.
-
E.
vehicleEligibility
Indicates whether a given vehicle satisfies the required conditions or criteria to be considered eligible for a specified purpose or program.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301a8198819092daa1c847889a88 |
completed | April 21, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3 p.m.