Triple
T19223226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guess Who? portrait series |
E480670
|
entity |
| Predicate | visualDevice |
P135246
|
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: [Guess Who? portrait series, visualDevice, figure–ground reversal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualDevice Context triple: [Guess Who? portrait series, visualDevice, figure–ground reversal]
-
A.
visualTechnology
Indicates a relationship where one entity is a technology used to capture, process, display, or otherwise handle visual information for another entity or context.
-
B.
portraysDevice
Indicates that one entity visually represents or depicts a device in some medium or context.
-
C.
visualCompanion
Indicates that one entity serves as a visual counterpart, partner, or accompanying element to another in a visual context.
-
D.
displayController
Indicates a relationship where one entity manages or controls the visual output or presentation of information on a display device for another entity.
-
E.
visualDepictionOnScreen
Indicates that one entity is visually shown or rendered on a screen as a depiction of another entity.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa94aed081909045cfed8edc6039 |
completed | April 20, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4debc39ac81908b7c5ef797046360 |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 1:24 p.m.