Triple
T7215431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aphrodite of Knidos |
E149518
|
entity |
| Predicate | portraysPose |
P15582
|
FINISHED |
| Object | contrapposto |
—
|
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: contrapposto | Statement: [Aphrodite of Knidos, portraysPose, contrapposto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysPose Context triple: [Aphrodite of Knidos, portraysPose, contrapposto]
-
A.
showsPose
chosen
Indicates that one entity displays or presents a particular pose or bodily posture of another entity.
-
B.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
C.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
D.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
E.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation 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_69c687eca814819095abb52316b1af80 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e98ebe1c81909891b4a1c2c3a4aa |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:53 p.m.