Triple
T3232541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW i3 |
E67772
|
entity |
| Predicate | passengerCellMaterial |
P19785
|
FINISHED |
| Object | carbon-fiber-reinforced plastic |
—
|
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: carbon-fiber-reinforced plastic | Statement: [BMW i3, passengerCellMaterial, carbon-fiber-reinforced plastic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerCellMaterial Context triple: [BMW i3, passengerCellMaterial, carbon-fiber-reinforced plastic]
-
A.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
B.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
C.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
D.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
E.
fuelTankMaterial
Indicates the material from which a fuel tank is made.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaedb718c8190aae12f763033713a |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0dc2248190a38c40f4e06cd41c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.