Triple
T31265163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sagaing Hills |
E797233
|
entity |
| Predicate | hasNunneryCountApprox |
P195143
|
FINISHED |
| Object | dozens of nunneries |
—
|
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: dozens of nunneries | Statement: [Sagaing Hills, hasNunneryCountApprox, dozens of nunneries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNunneryCountApprox Context triple: [Sagaing Hills, hasNunneryCountApprox, dozens of nunneries]
-
A.
numberOfNuns
Indicates the quantity or count of nuns associated with a given entity.
-
B.
hasMonasteryCountApprox
Indicates that an entity is associated with an approximate number of monasteries, rather than an exact count.
-
C.
hasChapelCountApprox
Indicates an approximate number of chapels associated with an entity.
-
D.
hadNunnery
Indicates that a location or institution possessed or hosted a nunnery at some point in time.
-
E.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
- 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_69f224de2bbc819081af6c32e1d857b9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
| PDg | Predicate description generation | batch_69fda945e1e08190bf923fcd4d2c548a |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 29, 2026, 9:12 p.m.