Triple
T4063376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wild nights—Wild nights! |
E86266
|
entity |
| Predicate | settingImagery |
P17123
|
FINISHED |
| Object | sea |
—
|
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: sea | Statement: [Wild nights—Wild nights!, settingImagery, sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingImagery Context triple: [Wild nights—Wild nights!, settingImagery, sea]
-
A.
usesImageryOf
chosen
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
-
B.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
C.
mapColor
Indicates a relationship where a map region or area is assigned or associated with a specific color, typically for visualization or categorization purposes.
-
D.
mapsTo
Indicates that one entity is associated with or transformed into another entity, typically defining a directional correspondence or function from a source to a target.
-
E.
imagedBy
Indicates that something is captured, recorded, or represented in an image created by a particular imaging device, method, or agent.
- 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.