Triple
T15438758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diana Leaving the Bath |
E369841
|
entity |
| Predicate | depictsCharacteristic |
P53700
|
FINISHED |
| Object | intimate scene |
—
|
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: intimate scene | Statement: [Diana Leaving the Bath, depictsCharacteristic, intimate scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsCharacteristic Context triple: [Diana Leaving the Bath, depictsCharacteristic, intimate scene]
-
A.
depictsAttribute
chosen
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
B.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
C.
depictsName
Indicates that something visually represents or portrays the name of an entity.
-
D.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
-
E.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edca064819081510bf303271062 |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.