Triple
T15842077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GT World Challenge Europe |
E384123
|
entity |
| Predicate | tyreSupplier |
P30565
|
FINISHED |
| Object | Pirelli |
E188558
|
NE 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: Pirelli | Statement: [GT World Challenge Europe, tyreSupplier, Pirelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pirelli Context triple: [GT World Challenge Europe, tyreSupplier, Pirelli]
-
A.
Pirelli
chosen
Pirelli is an Italian multinational company best known as one of the world’s leading manufacturers of high-performance tyres, particularly in motorsport and premium road vehicles.
-
B.
Michelin
Michelin is a major French multinational tire manufacturer renowned for its tires, travel guides, and the Michelin star restaurant rating system.
-
C.
Bridgestone
Bridgestone is a global tire and rubber company headquartered in Japan, known for its extensive involvement in motorsports and major sports sponsorships.
-
D.
Continental Motors
Continental Motors is an American manufacturer best known for producing aircraft and military vehicle engines, including powerplants for tanks and other armored vehicles.
-
E.
Pirelli DP-L10
The Pirelli DP-L10 is a GSM mobile phone handset commonly used as a low-cost, supported platform for open-source baseband experimentation and development.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa13eab4881908794104508ba53af |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 4:50 a.m.