Triple
T14935184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bust of Voltaire |
E372370
|
entity |
| Predicate | depictionAgeOfSubject |
P13483
|
FINISHED |
| Object | old age |
—
|
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: old age | Statement: [Bust of Voltaire, depictionAgeOfSubject, old age]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictionAgeOfSubject Context triple: [Bust of Voltaire, depictionAgeOfSubject, old age]
-
A.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
B.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
C.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
depictsAgeContrast
Indicates a relationship where one entity visually represents or highlights a contrast in age between two or more entities.
-
E.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded647ae388190a0e97c03f2a4d832 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:37 a.m.