Triple
T548759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Madame Récamier |
E12789
|
entity |
| Predicate | hasBackground |
P15585
|
FINISHED |
| Object | sparse interior |
—
|
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: sparse interior | Statement: [Portrait of Madame Récamier, hasBackground, sparse interior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackground Context triple: [Portrait of Madame Récamier, hasBackground, sparse interior]
-
A.
typicalBackground
Indicates that an entity has a usual or commonly expected background, context, or setting associated with it.
-
B.
hasFamilyBackgroundIn
Indicates that an entity comes from, or is associated with, a particular familial or ancestral background.
-
C.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
D.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
E.
hasFront
Indicates that an entity possesses or is associated with a front-facing side, surface, or portion.
- F. None of above. chosen
Provenance (4 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49900895c819092a131c185a758bf |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49858abd48190bd4b002a93e4a908 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.