Triple
T28799638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wen River |
E727194
|
entity |
| Predicate | hasWaterUseType |
P68556
|
FINISHED |
| Object | surface irrigation source |
—
|
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: surface irrigation source | Statement: [Wen River, hasWaterUseType, surface irrigation source]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterUseType Context triple: [Wen River, hasWaterUseType, surface irrigation source]
-
A.
hasWaterUse
chosen
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
-
B.
waterUse
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
-
C.
hasWatershedUse
Indicates that a particular type of use, activity, or function is associated with or applied to a watershed.
-
D.
hasRiverUse
Indicates that one entity makes use of a river associated with another entity, such as for transport, irrigation, recreation, or other purposes.
-
E.
usesWaterStorage
Indicates that an entity relies on or incorporates stored water as part of its operation, function, or process.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 28, 2026, 6:26 a.m.