Triple
T8242065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aconcagua wine region |
E192559
|
entity |
| Predicate | typicalIrrigation |
P79075
|
FINISHED |
| Object | drip irrigation |
—
|
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: drip irrigation | Statement: [Aconcagua wine region, typicalIrrigation, drip irrigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalIrrigation Context triple: [Aconcagua wine region, typicalIrrigation, drip irrigation]
-
A.
typeOfIrrigation
chosen
Indicates the specific irrigation method or system used to supply water to a given area or crop.
-
B.
usedIrrigation
Indicates that an entity applied or employed an irrigation system or method to supply water to land or crops.
-
C.
hasIrrigation
Indicates that an entity is equipped with or benefits from an irrigation system supplying water.
-
D.
irrigates
Indicates that one entity supplies water to another, typically land or crops, for the purpose of supporting growth or maintaining moisture.
-
E.
hasIrrigationArea
Indicates that an entity possesses or is associated with a specific area of land equipped or designated for irrigation.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb783f67708190a4e1c4078c3a6fb0 |
completed | March 31, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.