Triple
T17321738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2012 United States Grand Prix |
E420576
|
entity |
| Predicate | winningMarginSeconds |
P117596
|
FINISHED |
| Object | 0.675 |
—
|
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: 0.675 | Statement: [2012 United States Grand Prix, winningMarginSeconds, 0.675]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningMarginSeconds Context triple: [2012 United States Grand Prix, winningMarginSeconds, 0.675]
-
A.
finalRoundMargin
Indicates the point or score difference between competitors in the final round of a contest or competition.
-
B.
averageMarginOfVictory
Indicates the typical point or score difference by which one competitor or team wins over opponents across a set of contests or games.
-
C.
scoreMargin
chosen
Indicates the difference in score between two competitors or sides in a contest or game.
-
D.
originalWinningTime
Indicates the time originally recorded as the winning performance in a competition or event.
-
E.
winningTeamScore
Indicates the number of points or goals achieved by the team that wins a particular game 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439cf5394819089bff5f8dc2e8241 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.