Triple
T37268651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley-Davidson Night Train |
E924453
|
entity |
| Predicate | hasExhaustStyle |
P193913
|
FINISHED |
| Object | low-slung exhaust |
—
|
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: low-slung exhaust | Statement: [Harley-Davidson Night Train, hasExhaustStyle, low-slung exhaust]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExhaustStyle Context triple: [Harley-Davidson Night Train, hasExhaustStyle, low-slung exhaust]
-
A.
hasExteriorStyle
Indicates that an entity possesses or is characterized by a particular exterior design or stylistic appearance.
-
B.
hasStationStyle
Indicates that one entity (typically a station) possesses or is characterized by a particular architectural or design style.
-
C.
hasSternType
Indicates that an entity (typically a vessel) possesses a specific type or design of stern.
-
D.
hasTrainStyle
Indicates that one entity (typically a train or rail service) is characterized by or associated with a particular style, type, or configuration of train.
-
E.
hasParkStyle
Indicates that an entity possesses or is characterized by a particular style or type of park.
- 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_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
| PDg | Predicate description generation | batch_69fd592cc56081908ce456114d407616 |
completed | May 8, 2026, 3:31 a.m. |
Created at: May 3, 2026, 4:15 p.m.