Triple
T3878389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ker-Xavier Roussel |
E92559
|
entity |
| Predicate | depictedTheme |
P7671
|
FINISHED |
| Object | family life |
—
|
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: family life | Statement: [Ker-Xavier Roussel, depictedTheme, family life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictedTheme Context triple: [Ker-Xavier Roussel, depictedTheme, family life]
-
A.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
B.
eraDepicted
Indicates that a work or representation portrays, illustrates, or is set in a particular historical era or time period.
-
C.
commonlyDepictedOn
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
D.
depictsGenre
Indicates that one entity visually represents or portrays the genre category associated with another entity.
-
E.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.