Triple
T2013519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swans Reflecting Elephants |
E43740
|
entity |
| Predicate | hasVisualEffect |
P16366
|
FINISHED |
| Object | figure-ground reversal |
—
|
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: figure-ground reversal | Statement: [Swans Reflecting Elephants, hasVisualEffect, figure-ground reversal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualEffect Context triple: [Swans Reflecting Elephants, hasVisualEffect, figure-ground reversal]
-
A.
visualEffect
chosen
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
B.
hasVisualIndicator
Indicates that an entity is associated with some form of visual cue or marker that signals its status, condition, or presence.
-
C.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
D.
involvedPhysicalEffect
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
-
E.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b42d508190bf2b63132bb2ad77 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.