Triple
T1049703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class 220 Voyager |
E22665
|
entity |
| Predicate | carBodyConstruction |
P19785
|
FINISHED |
| Object | steel |
—
|
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: steel | Statement: [Class 220 Voyager, carBodyConstruction, steel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carBodyConstruction Context triple: [Class 220 Voyager, carBodyConstruction, steel]
-
A.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
B.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
C.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
D.
chassis
Indicates that one entity serves as the structural frame or supporting base (chassis) for another entity.
-
E.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.