Triple
T20078250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Las Tres Gracias |
E499927
|
entity |
| Predicate | depictsNude |
P101247
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Las Tres Gracias, depictsNude, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsNude Context triple: [Las Tres Gracias, depictsNude, true]
-
A.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
B.
nudity
chosen
Indicates that an entity is unclothed or exposes parts of the body typically covered, representing a state or depiction of being nude.
-
C.
primarySourceDepiction
Indicates that one entity serves as the main or authoritative visual or representational source depicting another entity.
-
D.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
E.
portrayalBodyDoubleForSomeShots
Indicates that one person served as a body double for another person in certain shots of a portrayal or performance.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643e216c819088c002fc1de2772a |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.