Triple
T20874036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inverted Boomerang |
E513969
|
entity |
| Predicate | trainMounting |
P142198
|
FINISHED |
| Object | articulated bogies below the track |
—
|
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: articulated bogies below the track | Statement: [Inverted Boomerang, trainMounting, articulated bogies below the track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainMounting Context triple: [Inverted Boomerang, trainMounting, articulated bogies below the track]
-
A.
mountVehicle
Indicates initiating the action of getting onto or into a vehicle in order to use or ride it.
-
B.
runnerMounting
Indicates a relationship where a runner is being attached, installed, or positioned onto another object or surface.
-
C.
mountingLocation
Indicates the physical position or surface on which something is attached, fixed, or installed.
-
D.
hasMountingFeature
Indicates that one entity includes or provides a structural feature intended for mounting or attaching another entity.
-
E.
mountOf
Indicates that one entity serves as the mount or riding animal/creature used by another entity.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c46639308190a616193f3975d453 |
completed | April 21, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:45 p.m.