Triple
T22749530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R179 |
E562655
|
entity |
| Predicate | hasCrashEnergyManagementFeatures |
P59968
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [R179, hasCrashEnergyManagementFeatures, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrashEnergyManagementFeatures Context triple: [R179, hasCrashEnergyManagementFeatures, yes]
-
A.
hasEnergyManagement
Indicates that an entity possesses or is associated with a system, capability, or function for monitoring, controlling, or optimizing energy use.
-
B.
hasEmergencyFeature
Indicates that an entity includes or supports a special function or capability intended for use in emergency situations.
-
C.
hasSurvivabilityFeature
chosen
Indicates that an entity possesses a characteristic, design element, or capability intended to enhance its ability to endure, resist damage, or remain functional under adverse conditions.
-
D.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
E.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b822988190b5368ac1f4e1d70a |
completed | April 29, 2026, 3:23 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:24 p.m.