Triple
T21255833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Badung |
E523864
|
entity |
| Predicate | nearbySector |
P85695
|
FINISHED |
| Object | tourism sector of Bali |
—
|
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: tourism sector of Bali | Statement: [Central Badung, nearbySector, tourism sector of Bali]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbySector Context triple: [Central Badung, nearbySector, tourism sector of Bali]
-
A.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
B.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
C.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
D.
nearbyFrontier
Indicates that one entity is located close to a boundary or frontier region associated with another entity.
-
E.
nearbyRegionCharacterizedBy
chosen
Indicates that a region located nearby another entity is defined or distinguished by a particular characteristic, feature, or condition.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735a1f9e08190b494f582bcae5c35 |
completed | April 21, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:58 p.m.