Triple
T37268885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley-Davidson Wide Glide |
E924459
|
entity |
| Predicate | frontEndType |
P188854
|
FINISHED |
| Object | wide-glide front end |
—
|
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: wide-glide front end | Statement: [Harley-Davidson Wide Glide, frontEndType, wide-glide front end]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontEndType Context triple: [Harley-Davidson Wide Glide, frontEndType, wide-glide front end]
-
A.
typeOfFront
Indicates that one entity is a specific kind or category of front (e.g., weather or battle front) relative to another.
-
B.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
C.
frontEnd
Indicates that one entity serves as the user-facing or client-side component in relation to another system or application.
-
D.
frontEndFor
Indicates that one entity serves as the user-facing interface or access point through which another underlying system, service, or component is used or interacted with.
-
E.
frontSightType
Indicates the specific kind or design of the front sight used on an object, typically a firearm or similar aiming device.
- F. None of above. chosen
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_69f76eacdd8c819094080d3991e6d37c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbad1b3ba08190ad69e21461333f2e |
completed | May 6, 2026, 9:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.