Triple
T30646095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brands Hatch |
E780122
|
entity |
| Predicate | GrandPrixCircuitLengthKm |
P170473
|
FINISHED |
| Object | 3.916 |
—
|
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: 3.916 | Statement: [Brands Hatch, GrandPrixCircuitLengthKm, 3.916]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GrandPrixCircuitLengthKm Context triple: [Brands Hatch, GrandPrixCircuitLengthKm, 3.916]
-
A.
grandPrixName
Indicates the official name assigned to a particular Grand Prix event.
-
B.
MonacoGrandPrixLocation
Indicates that a specified location is the venue where the Monaco Grand Prix takes place.
-
C.
previousF1FrenchGPLocation
Indicates that one location served as the venue for the immediately preceding Formula 1 French Grand Prix relative to another referenced race or event.
-
D.
grandPrixNumberInHistory
Indicates the ordinal position of a particular Grand Prix within the overall historical sequence of all Grand Prix events.
-
E.
raceWinCircuit
Indicates that an entity wins a race that takes place on a specific 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_69f224a5d2b481908a6853cd0138e2d7 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f69063edbc81909e7735954aabee0b |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68f6584a88190a8c4d95c0c84bee9 |
completed | May 2, 2026, 11:57 p.m. |
Created at: April 29, 2026, 8:29 p.m.