Triple
T18156383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirabeau |
E434640
|
entity |
| Predicate | hasOvertakingOpportunity |
P42383
|
FINISHED |
| Object | braking zone into the corner |
—
|
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: braking zone into the corner | Statement: [Mirabeau, hasOvertakingOpportunity, braking zone into the corner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOvertakingOpportunity Context triple: [Mirabeau, hasOvertakingOpportunity, braking zone into the corner]
-
A.
overtakingOpportunities
chosen
Indicates situations or conditions in which one entity can pass or move ahead of another within a shared path, route, or process.
-
B.
hasRightOfWay
Indicates that one entity is entitled to proceed or act before another in a shared space or interaction, without having to yield.
-
C.
safetyCarPossible
Indicates that conditions are such that deploying a safety car is a valid or allowable option.
-
D.
hasRightOfWaySeparation
Indicates that one entity is required to maintain a specified right-of-way distance or separation from another entity.
-
E.
hasLightningLane
Indicates that an attraction, experience, or location offers access via a Lightning Lane queue or reservation system.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debe27a88190bd76c6f78fcf1bd1 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.