Triple
T1351301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curicó Basin |
E28887
|
entity |
| Predicate | supportsProductionOf |
P490
|
FINISHED |
| Object | wine grapes |
—
|
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: wine grapes | Statement: [Curicó Basin, supportsProductionOf, wine grapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsProductionOf Context triple: [Curicó Basin, supportsProductionOf, wine grapes]
-
A.
increasesProductionOf
Indicates that one entity causes a rise or enhancement in the amount or rate at which another entity is produced.
-
B.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
C.
produces
chosen
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
D.
producesFor
Indicates that one entity creates, manufactures, or generates something specifically intended for another entity’s use, benefit, or distribution.
-
E.
massProduced
Indicates that an item is manufactured in large quantities, typically using standardized, industrial production processes.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26b1b4881908ae4b1b2c9b268a0 |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.