Triple
T15951916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TGV V150 |
E386837
|
entity |
| Predicate | wheelDiameterModification |
P121096
|
FINISHED |
| Object | increased wheel diameter for higher speed |
—
|
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: increased wheel diameter for higher speed | Statement: [TGV V150, wheelDiameterModification, increased wheel diameter for higher speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wheelDiameterModification Context triple: [TGV V150, wheelDiameterModification, increased wheel diameter for higher speed]
-
A.
wheelDiameter
Indicates the size of a wheel measured across its diameter.
-
B.
formerWheelDiameter
Indicates that one entity was previously the wheel diameter of another entity, but is no longer its current wheel diameter.
-
C.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
D.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
-
E.
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.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:53 a.m.