Triple
T29562617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Galaxie |
E750076
|
entity |
| Predicate | brakeTypeTypical |
P4166
|
FINISHED |
| Object | drum brakes (early years) |
—
|
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: drum brakes (early years) | Statement: [Ford Galaxie, brakeTypeTypical, drum brakes (early years)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brakeTypeTypical Context triple: [Ford Galaxie, brakeTypeTypical, drum brakes (early years)]
-
A.
brakeType
chosen
Indicates the specific kind or system of brakes associated with an entity.
-
B.
brakeFeature
Indicates that an entity possesses or is equipped with a particular braking-related feature or capability.
-
C.
brakeSupplier
Indicates that one entity serves as the supplier or provider of brakes to another entity.
-
D.
brakeWear
Indicates that an entity is experiencing or exhibiting wear, degradation, or reduction in effectiveness of its braking components or braking function.
-
E.
typicalTractionType
Indicates the usual or most common type of traction mechanism associated with an entity (such as how it is typically powered or driven).
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66d1e64e8819080579603e5bcdeb7 |
completed | May 2, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 5:21 p.m.