Triple
T3050337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École primaire de Prévessin |
E83551
|
entity |
| Predicate | partOfEducationSystem |
P340
|
FINISHED |
| Object | French education system |
—
|
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: French education system | Statement: [École primaire de Prévessin, partOfEducationSystem, French education system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfEducationSystem Context triple: [École primaire de Prévessin, partOfEducationSystem, French education system]
-
A.
educationSystem
chosen
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
B.
partOfStudy
Indicates that something is a component, segment, or subset within a larger study or research project.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
educationSetting
Indicates the type or context of the educational environment in which the related entity participates or operates.
-
E.
educationSystemCharacteristic
Indicates a characteristic, feature, or attribute that describes an education system.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bb1a46081908547a2f27cbf3446 |
completed | March 8, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.