Triple
T35211629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siyam Nikaya |
E1016694
|
entity |
| Predicate | mainMonasteriesLocatedIn |
P132651
|
FINISHED |
| Object | Kandy |
—
|
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: Kandy | Statement: [Siyam Nikaya, mainMonasteriesLocatedIn, Kandy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMonasteriesLocatedIn Context triple: [Siyam Nikaya, mainMonasteriesLocatedIn, Kandy]
-
A.
monasteriesAre
Indicates that a subject is classified as, functions as, or is identified with monasteries.
-
B.
numberOfActiveMonasteries
Indicates the count of monasteries that are currently active or operational in a given context.
-
C.
mainMonasteryLocation
chosen
Indicates the place where a religious order’s primary or central monastery is situated.
-
D.
monasticCenters
Indicates that one entity serves as a monastic center or hub for religious monastic life in relation to another entity.
-
E.
numberOfMonasteriesFounded
Indicates the total count of monasteries that a given entity has established or founded.
- 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78f63c8788190b253a18de5ca1312 |
completed | May 3, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:02 p.m.