Triple
T18435711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cindy Crawford as George Washington cover (first issue) |
E450384
|
entity |
| Predicate | visualConcept |
P89812
|
FINISHED |
| Object | politics as entertainment |
—
|
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: politics as entertainment | Statement: [Cindy Crawford as George Washington cover (first issue), visualConcept, politics as entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualConcept Context triple: [Cindy Crawford as George Washington cover (first issue), visualConcept, politics as entertainment]
-
A.
visualMetaphor
Indicates a relationship where one entity conceptually represents or explains another through a visual analogy or symbolic imagery.
-
B.
vision
Indicates that an entity perceives another entity or object visually, using sight.
-
C.
visualFeature
Indicates a relationship where one entity possesses or exhibits a particular visual characteristic or attribute of another entity.
-
D.
conceptualMeaning
chosen
Indicates the abstract idea, concept, or underlying significance that something represents or conveys.
-
E.
visuallyDefines
Indicates that one entity establishes or clarifies the appearance, form, or visual characteristics of another entity.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0cd30c8190b8417c264e60d3a5 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:28 a.m.