Triple
T31035843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nucleo Radiomobile Carabinieri |
E790849
|
entity |
| Predicate | staffTraining |
P153131
|
FINISHED |
| Object | operational driving |
—
|
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: operational driving | Statement: [Nucleo Radiomobile Carabinieri, staffTraining, operational driving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: staffTraining Context triple: [Nucleo Radiomobile Carabinieri, staffTraining, operational driving]
-
A.
trainingSupport
Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
-
B.
trainingIn
chosen
Indicates that one entity is undergoing or receiving training within the context, program, or domain specified by another entity.
-
C.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
D.
providesTrainingFor
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
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_69f224c97a788190b5da1ead6038a74e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:59 p.m.