Triple
T9325099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian School of the Judiciary |
E224365
|
entity |
| Predicate | usesTrainingMethods |
P16019
|
FINISHED |
| Object | case‑based learning |
—
|
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: case‑based learning | Statement: [Italian School of the Judiciary, usesTrainingMethods, case‑based learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainingMethods Context triple: [Italian School of the Judiciary, usesTrainingMethods, case‑based learning]
-
A.
trainingMethod
chosen
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
B.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
C.
requiresTraining
Indicates that one entity can only be properly or legitimately used, performed, or engaged with if the other entity has first received appropriate training.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd36f77c808190aa5489c4305fd67d |
completed | April 1, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:38 p.m.