Triple
T13069753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F33 |
E329424
|
entity |
| Predicate | chassisCodeUsage |
P44383
|
FINISHED |
| Object | used internally by BMW to identify the 4 Series convertible |
—
|
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: used internally by BMW to identify the 4 Series convertible | Statement: [F33, chassisCodeUsage, used internally by BMW to identify the 4 Series convertible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chassisCodeUsage Context triple: [F33, chassisCodeUsage, used internally by BMW to identify the 4 Series convertible]
-
A.
chassisCode
chosen
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
B.
usedChassisFor
Indicates that one entity employed or incorporated another entity’s chassis as the structural base or framework for its construction or operation.
-
C.
chassisName
Indicates the designated name or identifier assigned to a chassis in a system or dataset.
-
D.
hasChassisType
Indicates that an entity is associated with or equipped with a specific type of chassis.
-
E.
chassis
Indicates that one entity serves as the structural frame or supporting base (chassis) for another entity.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ee6130819095d835e7ff6a8c5b |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.