Triple
T35696905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferapontov Monastery |
E1031466
|
entity |
| Predicate | painterOfMainFrescoes |
P61872
|
FINISHED |
| Object | Dionisy |
—
|
NE NERFINISHED |
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: Dionisy | Statement: [Ferapontov Monastery, painterOfMainFrescoes, Dionisy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: painterOfMainFrescoes Context triple: [Ferapontov Monastery, painterOfMainFrescoes, Dionisy]
-
A.
hasWallPaintingsOn
Indicates that wall paintings are present on or applied to a specified surface or structure.
-
B.
masterPainter
chosen
Indicates that one entity is recognized as a highly skilled, authoritative painter in relation to another or within a given context.
-
C.
artistOfMainAltarpiece
Indicates that one entity is the artist who created the main altarpiece associated with another entity (such as a church or chapel).
-
D.
ceilingFrescoTitle
Indicates that one entity is the title assigned to a ceiling fresco associated with another entity.
-
E.
hasMainAltarpiece
Indicates that an entity (typically a religious building or space) possesses a specific artwork or structure serving as its principal altarpiece.
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.