Triple
T29229329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kidane Mehret |
E741023
|
entity |
| Predicate | inspiredMonasteries |
P174390
|
FINISHED |
| Object | Kidane Mehret monasteries in Ethiopia |
—
|
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: Kidane Mehret monasteries in Ethiopia | Statement: [Kidane Mehret, inspiredMonasteries, Kidane Mehret monasteries in Ethiopia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inspiredMonasteries Context triple: [Kidane Mehret, inspiredMonasteries, Kidane Mehret monasteries in Ethiopia]
-
A.
monasteriesAre
Indicates that a subject is classified as, functions as, or is identified with monasteries.
-
B.
monastery
Indicates that an entity is or functions as a monastery, typically a religious community or building where monastics live and practice.
-
C.
monasticCenters
Indicates that one entity serves as a monastic center or hub for religious monastic life in relation to another entity.
-
D.
monasteryType
Indicates the specific kind or classification of a monastery in relation to its broader religious or organizational category.
-
E.
monasteryBuiltInto
Indicates that a monastery is physically constructed within, attached to, or integrated into a natural or man-made structure such as a cliff, cave, or building.
- 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_69f07cbb12bc81908c1971d9de9a8d2a |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6c20f209081909fb9ac8f95069f04 |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c125695c81909704c67bef4ce5b2 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 28, 2026, 12:18 p.m.