Triple
T35872654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoro Department |
E1037268
|
entity |
| Predicate | hasNotablePhenomenon |
—
|
GENERATED |
| Object | Lluvia de Peces |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotablePhenomenon Context triple: [Yoro Department, hasNotablePhenomenon, Lluvia de Peces]
-
A.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
B.
hasNotableImpressionOf
Indicates that one entity holds a particularly strong, memorable, or significant impression of another entity.
-
C.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
D.
isNotable
Indicates that an entity is recognized as significant, prominent, or worthy of attention within a particular context or domain.
-
E.
hasNotableIncident
chosen
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
- F. None of above.
Provenance (1 batch)
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_69f76e1e701c8190a4990d4978ce4fe6 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:06 p.m.