Triple
T35753209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Grand Prix |
E1033370
|
entity |
| Predicate | notableCircuitCharacteristicAtHockenheimringShortened |
P206038
|
FINISHED |
| Object | more stadium-focused layout |
—
|
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: more stadium-focused layout | Statement: [German Grand Prix, notableCircuitCharacteristicAtHockenheimringShortened, more stadium-focused layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCircuitCharacteristicAtHockenheimringShortened Context triple: [German Grand Prix, notableCircuitCharacteristicAtHockenheimringShortened, more stadium-focused layout]
-
A.
GrandPrixCircuitLengthKm
Indicates the total length, measured in kilometers, of a Grand Prix racing circuit.
-
B.
raceWinCircuit
Indicates that an entity wins a race that takes place on a specific circuit.
-
C.
lapsAtAlbertPark
Indicates that an entity completes or records laps at the Albert Park circuit.
-
D.
GrandPrixCircuitTurns
Indicates the number or configuration of turns present in a Grand Prix racing circuit.
-
E.
hasMotorRacingCircuit
Indicates that a location or entity possesses, contains, or is the site of a motor racing circuit.
- F. None of above. chosen
Provenance (4 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037ce53de881908cf14141cf3bc570 |
completed | May 12, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:06 p.m.