Triple
T16971628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of a Gentleman |
E411696
|
entity |
| Predicate | portrayedLocationContext |
P54861
|
FINISHED |
| Object | Parisian society |
—
|
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: Parisian society | Statement: [Portrait of a Gentleman, portrayedLocationContext, Parisian society]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedLocationContext Context triple: [Portrait of a Gentleman, portrayedLocationContext, Parisian society]
-
A.
portrayedByRealWorldLocation
Indicates that a fictional or represented location is depicted or substituted by an actual real-world location.
-
B.
portrayedInSetting
chosen
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
C.
placesInContext
Indicates that one entity situates, interprets, or frames another entity within a particular context or surrounding circumstances.
-
D.
depictionContext
Indicates the situational or environmental setting in which something is depicted or represented.
-
E.
plotLocation
Indicates the relationship between a creative work and the place or setting where its story or events occur.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ad04ac81909a11b45be567613a |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:31 a.m.