Triple
T26753004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ceremonial county of Northamptonshire |
E674593
|
entity |
| Predicate | hasMotorSportFacility |
P13462
|
FINISHED |
| Object | Silverstone Circuit |
—
|
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: Silverstone Circuit | Statement: [ceremonial county of Northamptonshire, hasMotorSportFacility, Silverstone Circuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMotorSportFacility Context triple: [ceremonial county of Northamptonshire, hasMotorSportFacility, Silverstone Circuit]
-
A.
hasMotorRacingCircuit
chosen
Indicates that a location or entity possesses, contains, or is the site of a motor racing circuit.
-
B.
isMotorSportEventIn
Indicates that a particular motorsport event takes place within a specified location or venue.
-
C.
hasMotorsportInvolvement
Indicates that an entity is involved in motorsport, such as through participation, organization, sponsorship, or other direct association with motor racing activities.
-
D.
hasMotorParks
Indicates that an entity provides or contains designated areas or facilities for parking motor vehicles.
-
E.
hasKartingTrack
Indicates that one entity possesses or includes a karting track as a facility or feature.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 3:54 a.m.