Triple
T13084459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cache la Poudre River |
E310293
|
entity |
| Predicate | hasWaterUseIssue |
P26834
|
FINISHED |
| Object | agricultural irrigation demands |
—
|
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: agricultural irrigation demands | Statement: [Cache la Poudre River, hasWaterUseIssue, agricultural irrigation demands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterUseIssue Context triple: [Cache la Poudre River, hasWaterUseIssue, agricultural irrigation demands]
-
A.
hasWaterUse
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
-
B.
hasWaterManagementIssue
chosen
Indicates that an entity experiences problems or challenges related to the control, distribution, quality, or availability of water.
-
C.
waterUse
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
-
D.
usesWaterTreatment
Indicates that an entity applies or relies on a water treatment process or system in its operations or activities.
-
E.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981361e8c819099376435aa3a7aa3 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:02 p.m.