Triple
T24190895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombardier Turbostar multiple units |
E599690
|
entity |
| Predicate | hasBodyshellType |
P19785
|
FINISHED |
| Object | aluminium bodyshell |
—
|
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: aluminium bodyshell | Statement: [Bombardier Turbostar multiple units, hasBodyshellType, aluminium bodyshell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyshellType Context triple: [Bombardier Turbostar multiple units, hasBodyshellType, aluminium bodyshell]
-
A.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
B.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
C.
hasHatchback
Indicates that one entity possesses or is characterized by having a hatchback-style vehicle or body type.
-
D.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
E.
hasUndercarriageType
Indicates the specific type or configuration of undercarriage that an object (typically a vehicle or machine) possesses.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:35 p.m.