Triple
T4635072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voroneț Monastery |
E101508
|
entity |
| Predicate | hasFrescoesFrom |
P23612
|
FINISHED |
| Object | 16th century |
—
|
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: 16th century | Statement: [Voroneț Monastery, hasFrescoesFrom, 16th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrescoesFrom Context triple: [Voroneț Monastery, hasFrescoesFrom, 16th century]
-
A.
hasFrescoes
chosen
Indicates that something contains or is adorned with fresco paintings as part of its structure or decoration.
-
B.
hasExhibitionsAbout
Indicates that one entity organizes or presents exhibitions whose subject matter concerns another entity.
-
C.
hasArtGallery
Indicates that one entity possesses, contains, or hosts an art gallery as part of its facilities or offerings.
-
D.
hasFrieze
Indicates that one entity features or is adorned with a frieze associated with another entity.
-
E.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a5ec8108190aeb1147a67bff057 |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.