Triple
T33112750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruinen |
E847372
|
entity |
| Predicate | hasFord |
P7735
|
FINISHED |
| Object | Ford of Bruinen |
—
|
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: Ford of Bruinen | Statement: [Bruinen, hasFord, Ford of Bruinen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFord Context triple: [Bruinen, hasFord, Ford of Bruinen]
-
A.
usedFordPlatformsFor
Indicates that something (such as a tool, technology, or component) is employed specifically for building, supporting, or operating Ford-related platforms.
-
B.
hasCarConstructor
Indicates that an entity is associated with a specific car constructor (manufacturer or builder) responsible for producing its car.
-
C.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
D.
hasVehicle
chosen
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
E.
hasConceptVehicle
Indicates that an entity is associated with or involves a particular vehicle concept (e.g., as its subject, example, or focus).
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:27 a.m.