Triple
T21754124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Il ratto d’Europa |
E536991
|
entity |
| Predicate | raffigura |
P118298
|
FINISHED |
| Object | rapimento della principessa Europa |
—
|
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: rapimento della principessa Europa | Statement: [Il ratto d’Europa, raffigura, rapimento della principessa Europa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raffigura Context triple: [Il ratto d’Europa, raffigura, rapimento della principessa Europa]
-
A.
trainedFigure
Indicates that one entity has been trained, coached, or otherwise prepared by another entity.
-
B.
publicFigure
Indicates that an entity is widely recognized by the public and holds a prominent or influential role in society, such as in politics, entertainment, or media.
-
C.
intendedToDepict
chosen
Indicates that one entity was purposefully created or selected in order to visually represent or portray another entity.
-
D.
featuresFigureOf
Indicates that one entity includes or presents another entity as a figure, illustration, or visual element.
-
E.
draws
Indicates that one entity creates a visual representation or image 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8c57508190b45fb974ef0ded10 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969e46088190b13d6e9025775ea3 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.