Triple
T15930772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V8 engine |
E386317
|
entity |
| Predicate | hasTypicalBankAngle |
P120592
|
FINISHED |
| Object | 90 degrees |
—
|
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: 90 degrees | Statement: [V8 engine, hasTypicalBankAngle, 90 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalBankAngle Context triple: [V8 engine, hasTypicalBankAngle, 90 degrees]
-
A.
leanAngle
Indicates the degree to which an entity is tilted or inclined away from a reference upright position.
-
B.
tiltingCapability
Indicates the ability of one entity to tilt or be tilted relative to another or to a reference orientation.
-
C.
dropAngle
Indicates the angle at which something is dropped or released relative to a reference direction or surface.
-
D.
hasWireAngle
Indicates that one entity has a wire oriented or positioned at a specific angle relative to another reference or component.
-
E.
hasTypicalVelocity
Indicates that an entity is associated with a characteristic or commonly observed speed at which it typically moves or operates.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e172b213e481909ee0c05e16229a26 |
completed | April 16, 2026, 11:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.