Triple
T15842846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 Japanese Grand Prix |
E384138
|
entity |
| Predicate | tyreRegulationIssue |
P120085
|
FINISHED |
| Object | teams initially started on wrong tyres |
—
|
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: teams initially started on wrong tyres | Statement: [2007 Japanese Grand Prix, tyreRegulationIssue, teams initially started on wrong tyres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tyreRegulationIssue Context triple: [2007 Japanese Grand Prix, tyreRegulationIssue, teams initially started on wrong tyres]
-
A.
usesSpecTyres
Indicates that an entity operates or performs an action using special or specified types of tyres.
-
B.
tyreBrand
Indicates the brand or manufacturer associated with a given tyre.
-
C.
tyreSupplier
Indicates that one entity supplies or provides tyres to another entity.
-
D.
tireType
Indicates the specific kind or category of tire associated with an entity.
-
E.
isRubberTyred
Indicates that something operates or is equipped with rubber tires rather than steel wheels or another type of running gear.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007869ae481909473ee220a7ccdb5 |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:50 a.m.