Triple
T35795431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Australian Grand Prix |
E1034817
|
entity |
| Predicate | gridThirdDriver |
P62307
|
FINISHED |
| Object | Sebastian Vettel |
—
|
NE NERFINISHED |
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: Sebastian Vettel | Statement: [2016 Australian Grand Prix, gridThirdDriver, Sebastian Vettel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gridThirdDriver Context triple: [2016 Australian Grand Prix, gridThirdDriver, Sebastian Vettel]
-
A.
thirdPlaceSeatCount
Indicates the number of seats allocated to the entity that finished in third place in a given ranking or competition.
-
B.
thirdElement
chosen
Indicates that one entity is the third element in an ordered sequence or tuple associated with another entity.
-
C.
thirdStation
Indicates that one entity is the third station in an ordered sequence or route relative to another entity.
-
D.
usesThirdRail
Indicates that an entity operates by drawing electric power from a third rail rather than from overhead lines or other power sources.
-
E.
thirdPlaceManufacturer
Indicates that the manufacturer is ranked third in position relative to other manufacturers in a specified context or competition.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a25431b481908e39e953b207b6be |
completed | May 3, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.