Triple
T790221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon River |
E16895
|
entity |
| Predicate | drainageAreaRank |
P17270
|
FINISHED |
| Object | largest river basin in the world |
—
|
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: largest river basin in the world | Statement: [Amazon River, drainageAreaRank, largest river basin in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drainageAreaRank Context triple: [Amazon River, drainageAreaRank, largest river basin in the world]
-
A.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
B.
drainageBasin
Indicates the area of land where all precipitation and surface water flow are collected and drained toward a particular river, lake, or other water body.
-
C.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
D.
rankInWorldByArea
chosen
Indicates the position of an entity in a global ordering based on its total area size.
-
E.
watershedArea
Indicates the total land area from which surface water drains into a particular water body or point in the drainage system.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7841b0c8190859ecd247e32c6ec |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:38 p.m.