Triple
T8534970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vinho Verde region |
E202054
|
entity |
| Predicate | traditionalTrainingSystem |
P11879
|
FINISHED |
| Object | pergola |
—
|
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: pergola | Statement: [Vinho Verde region, traditionalTrainingSystem, pergola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalTrainingSystem Context triple: [Vinho Verde region, traditionalTrainingSystem, pergola]
-
A.
trainingSystem
chosen
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
B.
trainingFormat
Indicates the specific method or medium through which training is delivered or conducted.
-
C.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
D.
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.
-
E.
trainingStandard
Indicates that one entity defines or adheres to an established set of criteria, procedures, or benchmarks used for training or instruction of another entity.
- 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6a295c88190a432a060ee73f04e |
completed | March 31, 2026, 3:22 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:17 p.m.