Triple
T12505620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friant Water Authority |
E298939
|
entity |
| Predicate | typeOfWaterDelivered |
P851
|
FINISHED |
| Object | irrigation water |
—
|
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: irrigation water | Statement: [Friant Water Authority, typeOfWaterDelivered, irrigation water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWaterDelivered Context triple: [Friant Water Authority, typeOfWaterDelivered, irrigation water]
-
A.
sourceOfWaterSupply
Indicates that one entity serves as the origin or provider of another entity’s water supply.
-
B.
waterType
chosen
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
C.
waterServiceType
Indicates the specific kind or category of water service provided or associated with an entity.
-
D.
waterSupplyShare
Indicates the proportion of a total water supply that is allocated to or used by a particular entity.
-
E.
waterAllocatedTo
Indicates that a specified amount or portion of water has been designated or assigned for use by a particular entity, location, or purpose.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfddf38819099263b8b1e804736 |
completed | April 10, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69d94d43b7008190af2648fe09fd6d23 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:57 p.m.