Triple
T19303171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Isabel do Rio Negro |
E482752
|
entity |
| Predicate | hasRiverineEnvironment |
P113686
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Santa Isabel do Rio Negro, hasRiverineEnvironment, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverineEnvironment Context triple: [Santa Isabel do Rio Negro, hasRiverineEnvironment, true]
-
A.
hasRiverineCharacteristic
Indicates that something possesses qualities, features, or conditions associated with rivers or river environments.
-
B.
hasRiparianZone
chosen
Indicates that an area is adjacent to and ecologically influenced by a body of water, forming its riparian (riverbank or shoreline) zone.
-
C.
hasRiverInfluence
Indicates that one entity affects or is affected by a river in terms of its characteristics, behavior, or conditions.
-
D.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
E.
hasAquaticEcosystem
Indicates that an entity possesses, contains, or is associated with an ecosystem primarily based in water (such as rivers, lakes, wetlands, or oceans).
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604c5903c819090b3f89c3f33b005 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.