Triple
T16919895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BVG Class F |
E410417
|
entity |
| Predicate | carBodyProfile |
P124724
|
FINISHED |
| Object | large-profile Berlin U-Bahn loading gauge |
—
|
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: large-profile Berlin U-Bahn loading gauge | Statement: [BVG Class F, carBodyProfile, large-profile Berlin U-Bahn loading gauge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carBodyProfile Context triple: [BVG Class F, carBodyProfile, large-profile Berlin U-Bahn loading gauge]
-
A.
carBodyStyle
Indicates the specific body configuration or design style that characterizes a car (e.g., sedan, hatchback, SUV).
-
B.
carbodyMaterial
Indicates the material from which a vehicle’s body or main structural shell is made.
-
C.
bodyTypeDepicted
Indicates that one entity visually represents or portrays the physical body type of another entity.
-
D.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
E.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cded2f8481909a20cc08b47e922e |
completed | April 18, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32d7aae948190bc238d765795688c |
completed | April 18, 2026, 7:06 a.m. |
Created at: April 10, 2026, 5:30 a.m.