Triple
T13975109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titus as a Young Man |
E336167
|
entity |
| Predicate | depictsHumanFigure |
P61746
|
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: [Titus as a Young Man, depictsHumanFigure, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsHumanFigure Context triple: [Titus as a Young Man, depictsHumanFigure, true]
-
A.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
B.
containsHumanFigures
chosen
Indicates that the subject includes one or more human figures within its content or composition.
-
C.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
D.
depictsPeopleFrom
Indicates that one entity visually represents or portrays people originating from or associated with another entity.
-
E.
depicts costume
Indicates that one entity visually represents or portrays the clothing or outfit associated with 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8fd6d48190a157eae8df3a2f3a |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.