Triple
T27961603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bathsheba at Her Bath |
E704590
|
entity |
| Predicate | depictsNudity |
P101247
|
FINISHED |
| Object | female nude |
—
|
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: female nude | Statement: [Bathsheba at Her Bath, depictsNudity, female nude]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsNudity Context triple: [Bathsheba at Her Bath, depictsNudity, female nude]
-
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.
containsAdultContent
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
-
E.
hasRomanticSceneAt
Indicates that a romantic scene occurs at a specific location or point in time within a work or context.
- 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 27, 2026, 7:32 p.m.