Triple
T20498616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Río Colorado |
E503241
|
entity |
| Predicate | hasIrrigatedAgriculture |
P140315
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Río Colorado, hasIrrigatedAgriculture, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIrrigatedAgriculture Context triple: [Río Colorado, hasIrrigatedAgriculture, true]
-
A.
hasIrrigation
Indicates that an entity is equipped with or benefits from an irrigation system supplying water.
-
B.
hasIrrigationArea
Indicates that an entity possesses or is associated with a specific area of land equipped or designated for irrigation.
-
C.
hasIrrigationDependence
Indicates that one entity relies on another entity or system to provide irrigation for its water needs.
-
D.
usedIrrigation
Indicates that an entity applied or employed an irrigation system or method to supply water to land or crops.
-
E.
typeOfIrrigation
Indicates the specific irrigation method or system used to supply water to a given area or crop.
- F. None of above. chosen
Provenance (4 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbff210819089900e9a35911f48 |
completed | April 20, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:35 a.m.