Triple
T15777545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azerbaijan Grand Prix |
E382526
|
entity |
| Predicate | lapCountApproximate |
P120290
|
FINISHED |
| Object | around 51 to 53 laps depending on 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: around 51 to 53 laps depending on layout | Statement: [Azerbaijan Grand Prix, lapCountApproximate, around 51 to 53 laps depending on layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lapCountApproximate Context triple: [Azerbaijan Grand Prix, lapCountApproximate, around 51 to 53 laps depending on layout]
-
A.
junctionCountApprox
Indicates an approximate count of junctions or connection points involved in or associated with the given entities.
-
B.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
-
C.
hasApproximateMemberCount
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
D.
hasApproximateBrickCount
Indicates that an entity is associated with an estimated or non-exact number of bricks.
-
E.
hasApproximateEntryCount
Indicates that an entity is associated with a number representing an estimated or non-exact count of its entries.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05199cd8881909462462cec34d35a |
completed | April 16, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e03cc871d0819085c0fc54de7984ff |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 4:47 a.m.