Triple
T13290811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Formula One season |
E316554
|
entity |
| Predicate | driversChampionTitleNumber |
P51155
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [2014 Formula One season, driversChampionTitleNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driversChampionTitleNumber Context triple: [2014 Formula One season, driversChampionTitleNumber, 2]
-
A.
driversChampionships
chosen
Indicates the number of drivers’ championship titles an entity has won or is associated with.
-
B.
driversChampionshipWin
Indicates that a driver has won the overall drivers’ championship title in a given racing series or season.
-
C.
driversTitleWinner
Indicates that the subject is the driver who won the drivers’ championship title in the referenced competition or season.
-
D.
wonDriversTitleIn
Indicates that a driver secured the drivers’ championship title in a specified competition or season.
-
E.
consecutiveTitleNumberForChampion
Indicates that the associated number represents how many titles a champion has won consecutively up to that point.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:27 p.m.