Triple
T18236082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Tire Motorsport Park |
E436678
|
entity |
| Predicate | mainCircuitLength |
P44364
|
FINISHED |
| Object | approximately 3.957 km |
—
|
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: approximately 3.957 km | Statement: [Canadian Tire Motorsport Park, mainCircuitLength, approximately 3.957 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCircuitLength Context triple: [Canadian Tire Motorsport Park, mainCircuitLength, approximately 3.957 km]
-
A.
circuitLength
chosen
Indicates the total measured length or distance of a circuit or closed path.
-
B.
approximateCircuitLengthMi
Indicates the approximate total length of a circuit, measured in miles.
-
C.
numberOfCircuits
Indicates the total count of circuits associated with or contained in a given entity or system.
-
D.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
E.
mainStraightLengthM
Indicates the length, measured in meters, of the main straight segment (typically of a track, road, or similar linear 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b69a688190b140961eb298c36e |
completed | April 19, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69e4332336cc8190808b9c70c888ba65 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:33 a.m.