Triple
T14372678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zodiac Sea Wolf |
E356393
|
entity |
| Predicate | typicalLugWidth |
P113775
|
FINISHED |
| Object | 20 mm (approximate, varies by reference) |
—
|
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: 20 mm (approximate, varies by reference) | Statement: [Zodiac Sea Wolf, typicalLugWidth, 20 mm (approximate, varies by reference)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLugWidth Context triple: [Zodiac Sea Wolf, typicalLugWidth, 20 mm (approximate, varies by reference)]
-
A.
carWidth
Indicates the measurement of how wide a car is across its lateral (side-to-side) dimension.
-
B.
wheelHeightApprox
Indicates that the height of a wheel is approximately equal to a specified value or to the height of another wheel.
-
C.
usesCarWidth
Indicates that one entity determines, measures, or constrains something based on the width of a car.
-
D.
wheelbase
Indicates the distance between the centers of the front and rear wheels of a vehicle.
-
E.
trackWidth
Indicates the lateral distance between two parallel tracks or wheels, typically measured from center to center.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb2082c8190b42cc5f2bab4f574 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:15 a.m.