Triple
T15969154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akananuru |
E387273
|
entity |
| Predicate | usesLandscapeImagery |
P17123
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Akananuru, usesLandscapeImagery, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLandscapeImagery Context triple: [Akananuru, usesLandscapeImagery, yes]
-
A.
usesImagery
Indicates that one entity employs descriptive or figurative language to create sensory or vivid mental images in relation to another entity or concept.
-
B.
usesImageryOf
chosen
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
-
C.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
D.
hasColorImagery
Indicates that something includes or is characterized by visual elements emphasizing specific colors or color-based symbolism.
-
E.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.