Triple
T3578428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koshi River |
E75742
|
entity |
| Predicate | drainageAreaInNepal |
P28955
|
FINISHED |
| Object | approximately 29000 square kilometres |
—
|
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: approximately 29000 square kilometres | Statement: [Koshi River, drainageAreaInNepal, approximately 29000 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drainageAreaInNepal Context triple: [Koshi River, drainageAreaInNepal, approximately 29000 square kilometres]
-
A.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
B.
drainageAreaApprox
chosen
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
C.
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.
-
D.
lakeArea
Indicates the surface area measurement of a lake.
-
E.
reservoirSurfaceArea
Indicates the total area covered by the surface of a reservoir.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0defe14819095a337a840e33300 |
completed | March 8, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.