Triple
T12863951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W. Kerr Scott Dam |
E307667
|
entity |
| Predicate | hasReservoirSurfaceArea |
P35437
|
FINISHED |
| Object | approximately 1,475 acres |
—
|
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 1,475 acres | Statement: [W. Kerr Scott Dam, hasReservoirSurfaceArea, approximately 1,475 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReservoirSurfaceArea Context triple: [W. Kerr Scott Dam, hasReservoirSurfaceArea, approximately 1,475 acres]
-
A.
reservoirSurfaceArea
chosen
Indicates the total area covered by the surface of a reservoir.
-
B.
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.
-
C.
hasAreaWaterBody
Indicates that an entity includes, contains, or is associated with a body of water within its area or boundaries.
-
D.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
E.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:37 p.m.