Triple
T6850717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Park Circuit |
E158006
|
entity |
| Predicate | hasChicanes |
P38721
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Albert Park Circuit, hasChicanes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChicanes Context triple: [Albert Park Circuit, hasChicanes, yes]
-
A.
hasStunts
Indicates that one entity performs, includes, or is associated with stunt actions for another entity or context.
-
B.
hasLightningLane
Indicates that an attraction, experience, or location offers access via a Lightning Lane queue or reservation system.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasSwitchbacks
chosen
Indicates that a path, road, or trail includes sharp, back-and-forth turns (zigzags) used to navigate steep terrain.
-
E.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
- 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_69c6882fae988190864cbba788c5ebb4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d84c45708190918adfc028252400 |
completed | March 27, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.