Triple
T17680892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Time |
E440764
|
entity |
| Predicate | isUsedInRiverRegion |
P73621
|
FINISHED |
| Object | Rio Negro region around Manaus |
—
|
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: Rio Negro region around Manaus | Statement: [Amazon Time, isUsedInRiverRegion, Rio Negro region around Manaus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedInRiverRegion Context triple: [Amazon Time, isUsedInRiverRegion, Rio Negro region around Manaus]
-
A.
locatedInRiverArea
chosen
Indicates that one entity is situated within the geographic area occupied by, adjacent to, or directly associated with a particular river.
-
B.
hasSettlementOnRiver
Indicates that a settlement is located on or directly adjacent to a specific river.
-
C.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
D.
hasRiverInfluence
Indicates that one entity affects or is affected by a river in terms of its characteristics, behavior, or conditions.
-
E.
riverRegion
Indicates that a river is located within, flows through, or is otherwise geographically associated with a particular region.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470445b3881908bb0930b986089f7 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.