Triple
T24732917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yavitero |
E618334
|
entity |
| Predicate | spokenInRiverBasin |
P72732
|
FINISHED |
| Object | Amazon River basin |
—
|
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: Amazon River basin | Statement: [Yavitero, spokenInRiverBasin, Amazon River basin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInRiverBasin Context triple: [Yavitero, spokenInRiverBasin, Amazon River basin]
-
A.
associatedRiverBasin
chosen
Indicates that one entity is linked to, or lies within the drainage area of, a particular river basin.
-
B.
riverMentioned
Indicates that a river is referenced or discussed in the given context or data.
-
C.
betweenRiver
Indicates a spatial relationship where something is located in the area separating two rivers or lies in the intermediate region defined by them.
-
D.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
E.
mouthOfTheWatercourse
Indicates the location where a watercourse ends and flows into a larger body of water.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:02 a.m.