Triple
T1561264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Ángeles Basin |
E33327
|
entity |
| Predicate | waterResourcesUse |
P19373
|
FINISHED |
| Object | irrigation for crops |
—
|
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 for crops | Statement: [Los Ángeles Basin, waterResourcesUse, irrigation for crops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterResourcesUse Context triple: [Los Ángeles Basin, waterResourcesUse, irrigation for crops]
-
A.
waterUse
chosen
Indicates the amount or manner in which water is consumed, utilized, or withdrawn by an entity or activity.
-
B.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
C.
waterInfrastructure
Indicates the existence, development, or management of systems and facilities that supply, store, treat, or distribute water between entities.
-
D.
waterAllocatedTo
Indicates that a specified amount or portion of water has been designated or assigned for use by a particular entity, location, or purpose.
-
E.
sourceOfWaterSupply
Indicates that one entity serves as the origin or provider of another entity’s water supply.
- 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_69a885ef9cf48190b0af0f5ce3d02231 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:27 p.m.