Triple
T20272391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMW Museum |
E502922
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | BMW AG |
—
|
NE NERFINISHED |
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: BMW AG | Statement: [BMW Museum, ownedBy, BMW AG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BMW AG Context triple: [BMW Museum, ownedBy, BMW AG]
-
A.
BMW M GmbH
BMW M GmbH is BMW's high-performance subsidiary responsible for developing and producing the brand’s sport-oriented M models and tuning packages.
-
B.
BMW
BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
-
C.
Bayerische Motoren Werke AG
chosen
Bayerische Motoren Werke AG is a German multinational company best known for producing premium automobiles and motorcycles under the BMW, MINI, and Rolls-Royce brands.
-
D.
Audi
"Audi" is a popular hip-hop track by American rapper Smokepurpp that helped boost his rise in the SoundCloud rap scene.
-
E.
Audi
Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675dff3c4819098ba45eba4e7b296 |
completed | April 20, 2026, 6:52 p.m. |
Created at: April 16, 2026, 10:15 a.m.