Triple
T36437472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelby GT500 (2020–2022) |
E897626
|
entity |
| Predicate | rearBrakeRotorDiameter |
P185497
|
FINISHED |
| Object | 14.6 in |
—
|
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: 14.6 in | Statement: [Shelby GT500 (2020–2022), rearBrakeRotorDiameter, 14.6 in]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearBrakeRotorDiameter Context triple: [Shelby GT500 (2020–2022), rearBrakeRotorDiameter, 14.6 in]
-
A.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
B.
hasRimDiameter
Indicates that one entity has a rim whose diameter is measured by or corresponds to the value or object represented by the other entity.
-
C.
wheelDiameter
Indicates the size of a wheel measured across its diameter.
-
D.
formerWheelDiameter
Indicates that one entity was previously the wheel diameter of another entity, but is no longer its current wheel diameter.
-
E.
trackDiameter
Indicates the diameter measurement of a track, typically specifying the width across its circular or rounded layout.
- 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_69f76e56636481908eda808ab0273401 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.