Triple
T18229200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endurance Circuit 2010 |
E436497
|
entity |
| Predicate | usageDuration |
P13716
|
FINISHED |
| Object | one Formula One Grand Prix weekend |
—
|
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: one Formula One Grand Prix weekend | Statement: [Endurance Circuit 2010, usageDuration, one Formula One Grand Prix weekend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageDuration Context triple: [Endurance Circuit 2010, usageDuration, one Formula One Grand Prix weekend]
-
A.
durationOfUse
chosen
Indicates the length of time for which something is used or remains in use.
-
B.
hasTypicalUseTime
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
-
C.
typicalUseDays
Indicates the usual or expected number of days over which something is used or intended to be used.
-
D.
usagePeak
Indicates that the usage or consumption of something reaches its highest level or intensity during a particular time or condition.
-
E.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f4b1b2108190a5585bbfaf2d295b |
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.