Triple
T28979245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Martin |
E734498
|
entity |
| Predicate | notableVehicleBrand |
P140875
|
FINISHED |
| Object | BMW |
E10671
|
NE 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: BMW | Statement: [Frank Martin, notableVehicleBrand, BMW]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVehicleBrand Context triple: [Frank Martin, notableVehicleBrand, BMW]
-
A.
notableCar
Indicates that the subject is a car recognized for its significance, prominence, or special interest (e.g., historically, culturally, or technically).
-
B.
carManufacturer
Indicates that one entity is the company that produces or manufactures the car represented by the other entity.
-
C.
vehicleBrandAssociated
chosen
Indicates that there is an association or linkage between a vehicle and a particular brand.
-
D.
notableManufacturer
Indicates that an entity is a well-known or prominent producer or maker of another entity.
-
E.
notableTrainBrand
Indicates that an entity is a well-known or significant brand associated with trains or railway services.
- F. None of above.
Provenance (4 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a01d077dcec8190b05b24b5de313b15 |
completed | May 11, 2026, 12:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a24ec62116c819093068ef068c177fd |
completed | June 7, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_6a01cea0e37881909cb6888518c6d12f |
completed | May 11, 2026, 12:42 p.m. |
Created at: April 28, 2026, 9:10 a.m.