Triple
T15790647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW i5 |
E382854
|
entity |
| Predicate | hasAdaptiveCruiseControl |
P67070
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [BMW i5, hasAdaptiveCruiseControl, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdaptiveCruiseControl Context triple: [BMW i5, hasAdaptiveCruiseControl, true]
-
A.
hasDriverAssistance
Indicates that an entity is equipped with or supports driver assistance features or systems.
-
B.
hasPassengerCongestionControls
Indicates that an entity includes mechanisms or measures to manage, limit, or alleviate congestion caused by passengers.
-
C.
hasVehicleFeature
chosen
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
D.
hasAutomaticTrainControl
Indicates that an entity is equipped with or uses an automatic train control system for managing train operations.
-
E.
hasAutomaticTrainControlCompatibility
Indicates that an entity is compatible with, or supports integration with, an automatic train control (ATC) system.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d819c881908bc43a6124a1bb2e |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:48 a.m.