Triple
T37268523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley-Davidson Fat Boy |
E924450
|
entity |
| Predicate | hasFrameAppearance |
P175674
|
FINISHED |
| Object | hardtail look |
—
|
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: hardtail look | Statement: [Harley-Davidson Fat Boy, hasFrameAppearance, hardtail look]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrameAppearance Context triple: [Harley-Davidson Fat Boy, hasFrameAppearance, hardtail look]
-
A.
hasFrameEffect
chosen
Indicates that one entity produces or is associated with a visual or stylistic frame-related effect on another entity.
-
B.
hasPanelAppearance
Indicates that an entity features or exhibits a particular panel-based visual or structural appearance.
-
C.
hasFrameElement
Indicates that a frame (or structured conceptual scenario) includes or is associated with a specific frame element (a participant, role, or component within that frame).
-
D.
hasFrameType
Indicates that an entity possesses or is associated with a specific type or category of frame.
-
E.
isFramedAs
Indicates that one entity is presented, interpreted, or characterized in terms of another particular perspective, context, or narrative.
- 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_69f76eacdd8c819094080d3991e6d37c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:15 p.m.