Triple
T31755039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boomerang roller coaster model |
E810534
|
entity |
| Predicate | trainDirectionChange |
P152646
|
FINISHED |
| Object | reverses direction mid-ride |
—
|
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: reverses direction mid-ride | Statement: [Boomerang roller coaster model, trainDirectionChange, reverses direction mid-ride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainDirectionChange Context triple: [Boomerang roller coaster model, trainDirectionChange, reverses direction mid-ride]
-
A.
transportDirection
Indicates the directional flow or route along which something is transported from an origin toward a destination.
-
B.
terminusDirection
Indicates the directional orientation or endpoint direction associated with a route, path, or line.
-
C.
trainNumberDirection
Indicates the specific direction in which a train, identified by its train number, is traveling or scheduled to travel.
-
D.
railwayTrafficDirection
Indicates the customary side of the track on which trains are operated or expected to run within a given railway system or segment.
-
E.
courseDirectionChange
chosen
Indicates a change in the direction or path of movement of an entity from its previous course.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 30, 2026, 11:29 p.m.