Triple
T7114847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montenegro and the Littoral |
E165791
|
entity |
| Predicate | hasMonasticCommunities |
P74629
|
FINISHED |
| Object | monks at Cetinje Monastery |
—
|
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: monks at Cetinje Monastery | Statement: [Montenegro and the Littoral, hasMonasticCommunities, monks at Cetinje Monastery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonasticCommunities Context triple: [Montenegro and the Littoral, hasMonasticCommunities, monks at Cetinje Monastery]
-
A.
monasticCenters
Indicates that one entity serves as a monastic center or hub for religious monastic life in relation to another entity.
-
B.
containsMonastery
Indicates that one entity includes or encompasses a monastery within its boundaries or composition.
-
C.
numberOfActiveMonasteries
Indicates the count of monasteries that are currently active or operational in a given context.
-
D.
monastery
Indicates that an entity is or functions as a monastery, typically a religious community or building where monastics live and practice.
-
E.
monasteryType
Indicates the specific kind or classification of a monastery in relation to its broader religious or organizational category.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5f0dab8819092103aefcaa1f9c2 |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e456e89481908df42a1b4232a4a0 |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2:43 p.m.