Triple
T8349845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bentley Flying Spur Speed |
E196131
|
entity |
| Predicate | drivingCharacter |
P82223
|
FINISHED |
| Object | combines comfort with dynamic performance |
—
|
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: combines comfort with dynamic performance | Statement: [Bentley Flying Spur Speed, drivingCharacter, combines comfort with dynamic performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingCharacter Context triple: [Bentley Flying Spur Speed, drivingCharacter, combines comfort with dynamic performance]
-
A.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
B.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
C.
drives
Indicates that one entity operates and controls the movement of a vehicle or similar conveyance transporting themselves or others.
-
D.
controllingCharacter
Indicates that one character exerts control, influence, or authority over another character.
-
E.
cycleCharacter
Indicates that one character in a sequence is followed by another in a repeating (cyclic) order.
- F. None of above. chosen
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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80181ca48190bbf2e6a6aae80d69 |
completed | March 31, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69cb70c6d0ec8190acf273b0e007b51a |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:59 p.m.