Triple
T38355105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovčar |
E1046304
|
entity |
| Predicate | hasMonasteryCluster |
P20652
|
FINISHED |
| Object | Ovčar-Kablar monasteries |
—
|
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: Ovčar-Kablar monasteries | Statement: [Ovčar, hasMonasteryCluster, Ovčar-Kablar monasteries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonasteryCluster Context triple: [Ovčar, hasMonasteryCluster, Ovčar-Kablar monasteries]
-
A.
hasMonasteryCountApprox
Indicates that an entity is associated with an approximate number of monasteries, rather than an exact count.
-
B.
hasMonasteryDedicatedTo
Indicates that a place or institution possesses a monastery whose religious dedication is to a specific figure, deity, or sacred concept.
-
C.
hasMonksResidence
Indicates that a place includes or is associated with a residence where monks live.
-
D.
containsMonastery
chosen
Indicates that one entity includes or encompasses a monastery within its boundaries or composition.
-
E.
hasMonasteryRuins
Indicates that an entity possesses or contains the remains or ruins of a former monastery.
- 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_69f76e3a94fc81908edc175e8d259e80 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffc516d1908190b475f5a6156b0ca8 |
completed | May 9, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69ffc4a946e08190b3535a5dc15ac484 |
completed | May 9, 2026, 11:35 p.m. |
Created at: May 3, 2026, 4:31 p.m.