Triple
T25902848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uma Mbatangu |
E652665
|
entity |
| Predicate | foundInSettlementType |
P44412
|
FINISHED |
| Object | traditional Sumbanese village |
—
|
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: traditional Sumbanese village | Statement: [Uma Mbatangu, foundInSettlementType, traditional Sumbanese village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundInSettlementType Context triple: [Uma Mbatangu, foundInSettlementType, traditional Sumbanese village]
-
A.
isLocatedInSettlement
chosen
Indicates that an entity is situated within or belongs to a specific human settlement, such as a town, village, or city.
-
B.
servedSettlementType
Indicates the type of settlement (e.g., city, town, village) that is provided service or coverage by a given entity.
-
C.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
D.
spokenInSettlementType
Indicates that a language or dialect is spoken within settlements of a specified type (e.g., city, village, town).
-
E.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 22, 2026, 8:26 a.m.