Triple
T16181175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentino Rossi |
E392685
|
entity |
| Predicate | premierClassWorldChampionshipTitles |
P15197
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Valentino Rossi, premierClassWorldChampionshipTitles, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: premierClassWorldChampionshipTitles Context triple: [Valentino Rossi, premierClassWorldChampionshipTitles, 7]
-
A.
numberOfF1WorldChampionships
Indicates the number of Formula 1 World Championship titles that an entity has won.
-
B.
grandPrixRaceWins
Indicates the number of Grand Prix races that an entity has won.
-
C.
numberOfFormulaOneTTWorldTitles
Indicates the count of Formula One TT World Championship titles that an entity has won.
-
D.
totalFormulaOneWins
Indicates the total number of Formula One race victories achieved by a given driver, team, or other relevant entity.
-
E.
worldChampionshipTitles
chosen
Indicates the number of world championship titles an entity has won.
- F. None of above.
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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205c92b48190b7125dbbcff3662e |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.