Triple
T17254869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loin de l’Oeil |
E418853
|
entity |
| Predicate | vineTrainingPreference |
P43323
|
FINISHED |
| Object | traditional bush vines |
—
|
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: traditional bush vines | Statement: [Loin de l’Oeil, vineTrainingPreference, traditional bush vines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vineTrainingPreference Context triple: [Loin de l’Oeil, vineTrainingPreference, traditional bush vines]
-
A.
typicalVineTraining
chosen
Indicates that one entity is the standard or commonly used method of training or shaping the growth of another entity, typically in a vine or climbing context.
-
B.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
C.
trainingDomain
Indicates that an entity is associated with or operates within a particular field, area, or domain of training.
-
D.
trainingUnder
Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
-
E.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6c362c819088965c6e05f33faf |
completed | April 19, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.