Triple
T4063352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wild nights—Wild nights! |
E86266
|
entity |
| Predicate | imageryType |
P34813
|
FINISHED |
| Object | maritime imagery |
—
|
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: maritime imagery | Statement: [Wild nights—Wild nights!, imageryType, maritime imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageryType Context triple: [Wild nights—Wild nights!, imageryType, maritime imagery]
-
A.
usesImageryOf
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
-
B.
evokesImageOf
Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
iconographyType
chosen
Indicates the specific kind or category of visual symbolism or imagery used to represent something.
-
E.
sightType
Indicates the specific kind or category of sight or visual perception associated with an entity or event.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0bdea48190805a79515ee92709 |
completed | March 9, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69aef90438908190a005b08ba271eacf |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.