Triple
T1051901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Trinity Monastery |
E22716
|
entity |
| Predicate | hasFrescoes |
P23612
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Holy Trinity Monastery, hasFrescoes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrescoes Context triple: [Holy Trinity Monastery, hasFrescoes, yes]
-
A.
hasFrieze
Indicates that one entity features or is adorned with a frieze associated with another entity.
-
B.
hasArtInstallation
Indicates that an entity features or contains an art installation as part of its space or composition.
-
C.
hasArtGallery
Indicates that one entity possesses, contains, or hosts an art gallery as part of its facilities or offerings.
-
D.
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.
-
E.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b5312081909796df58fa7c1e9d |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7f2d1b081908eb2df54e91c8c1d |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.