Triple
T30019289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ocheyedan River |
E762685
|
entity |
| Predicate | drainageAreaUse |
P107197
|
FINISHED |
| Object | corn production |
—
|
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: corn production | Statement: [Ocheyedan River, drainageAreaUse, corn production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drainageAreaUse Context triple: [Ocheyedan River, drainageAreaUse, corn production]
-
A.
basinUse
Indicates that a basin is used for a particular purpose, activity, or function.
-
B.
drainagePurpose
Indicates the intended function or reason for which a drainage system or feature is designed or used.
-
C.
drainsAreaOf
Indicates that one entity serves as a drainage outlet or basin for another entity, carrying away its surface or groundwater.
-
D.
drainageBasinLandUse
chosen
Indicates how the land within a drainage basin is utilized or managed (e.g., for agriculture, urban development, or natural vegetation).
-
E.
drainageAreaFeature
Indicates the geographic feature or area from which water drains into a particular water body or 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_69f2246b0c84819094f1250b6a02d277 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67986d50481909be55ada094f2ea1 |
completed | May 2, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 6:47 p.m.