Triple
T10325247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Mustang GT/CS |
E242745
|
entity |
| Predicate | automobileClass |
P69147
|
FINISHED |
| Object | pony car |
—
|
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: pony car | Statement: [Ford Mustang GT/CS, automobileClass, pony car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: automobileClass Context triple: [Ford Mustang GT/CS, automobileClass, pony car]
-
A.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
vehicleStandard
Indicates that something complies with, or is defined according to, a specified vehicle-related standard or regulatory specification.
-
C.
vehicleFamily
Indicates that two vehicles belong to the same family or category based on shared design, platform, or lineage.
-
D.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
E.
automotiveSegment
chosen
Indicates a classification relationship where an automotive product, brand, or activity is assigned to a specific market or vehicle segment within the automotive industry.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7cd76348190b93562112300acfc |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f64a648190a79980d647898eb0 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:51 a.m.