Triple
T15758352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian River (California) |
E382025
|
entity |
| Predicate | watershedAreaApprox |
P28955
|
FINISHED |
| Object | 1485 square miles |
—
|
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: 1485 square miles | Statement: [Russian River (California), watershedAreaApprox, 1485 square miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: watershedAreaApprox Context triple: [Russian River (California), watershedAreaApprox, 1485 square miles]
-
A.
watershedArea
Indicates the total land area from which surface water drains into a particular water body or point in the drainage system.
-
B.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
C.
drainageAreaApprox
chosen
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
D.
drainageAreaFeature
Indicates the geographic feature or area from which water drains into a particular water body or drainage system.
-
E.
hasTailwaterArea
Indicates that a water control structure (such as a dam or weir) is associated with a downstream tailwater area where water flows out and levels are influenced by the structure’s discharge.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b35ea48190a758ee76a57b5451 |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.