Triple
T9739068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaware Aqueduct |
E236139
|
entity |
| Predicate | waterConveyanceCapacity |
P14199
|
FINISHED |
| Object | about 890 million gallons per day |
—
|
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: about 890 million gallons per day | Statement: [Delaware Aqueduct, waterConveyanceCapacity, about 890 million gallons per day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterConveyanceCapacity Context triple: [Delaware Aqueduct, waterConveyanceCapacity, about 890 million gallons per day]
-
A.
waterInfrastructure
Indicates the existence, development, or management of systems and facilities that supply, store, treat, or distribute water between entities.
-
B.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
-
C.
usedWaterway
Indicates that one entity traveled, transported goods, or otherwise moved via a particular waterway as the route or medium of use.
-
D.
transportsWaterTo
chosen
Indicates that one entity carries or conveys water from its location or source to another entity or destination.
-
E.
inflowWatercourse
Indicates that one watercourse flows into or feeds another water body or watercourse.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ef43fec8190987628f401a27436 |
completed | April 1, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:22 p.m.