Triple
T7214920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrysler Pacifica |
E149506
|
entity |
| Predicate | hasSafetyTechnology |
P57273
|
FINISHED |
| Object | adaptive cruise control |
—
|
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: adaptive cruise control | Statement: [Chrysler Pacifica, hasSafetyTechnology, adaptive cruise control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyTechnology Context triple: [Chrysler Pacifica, hasSafetyTechnology, adaptive cruise control]
-
A.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
B.
hasDriverAssistance
chosen
Indicates that an entity is equipped with or supports driver assistance features or systems.
-
C.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
D.
hasNavigationTechnology
Indicates that an entity is equipped with or utilizes a system or technology for determining or guiding its position, route, or movement.
-
E.
hasSafetyInfrastructure
Indicates that appropriate safety-related structures, systems, or measures are present for the referenced entity or environment.
- 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_69c687eca814819095abb52316b1af80 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e98ebe1c81909891b4a1c2c3a4aa |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:53 p.m.