Triple
T13288316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Panorama Circuit |
E316498
|
entity |
| Predicate | hasCornerCount |
P109332
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Mount Panorama Circuit, hasCornerCount, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCornerCount Context triple: [Mount Panorama Circuit, hasCornerCount, 23]
-
A.
hasCorner
Indicates that one entity possesses or includes a corner that is part of or associated with another entity.
-
B.
hasSlowCorners
Indicates that an entity possesses corners or turning points that are navigated or traversed at a relatively low speed.
-
C.
hasFastCorners
Indicates that an object, route, or structure includes corners or turns that can be navigated at high speed.
-
D.
tracksPerCorner
Indicates the number of distinct tracks or lanes associated with each corner in a layout or design.
-
E.
hasRightAngleIntersections
Indicates that the entities intersect each other at right (90-degree) angles.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:27 p.m.