Triple
T7024451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chile's Central Valley wine region |
E162907
|
entity |
| Predicate | typicalTrainingSystem |
P11879
|
FINISHED |
| Object | vertical shoot positioning |
—
|
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: vertical shoot positioning | Statement: [Chile's Central Valley wine region, typicalTrainingSystem, vertical shoot positioning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrainingSystem Context triple: [Chile's Central Valley wine region, typicalTrainingSystem, vertical shoot positioning]
-
A.
typicalTraining
Indicates that an entity commonly undergoes or is associated with a standard or usual form of training in relation to another entity or context.
-
B.
trainingSystem
chosen
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
C.
trainingBase
Indicates that one entity serves as the training base, site, or facility where another entity receives training or instruction.
-
D.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
E.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:35 p.m.