Triple
T27638254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe à plusieurs vitesses |
E696521
|
entity |
| Predicate | exempleTypique |
P67300
|
FINISHED |
| Object | zone euro |
—
|
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: zone euro | Statement: [Europe à plusieurs vitesses, exempleTypique, zone euro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exempleTypique Context triple: [Europe à plusieurs vitesses, exempleTypique, zone euro]
-
A.
exampleType
chosen
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
-
D.
typicalFunction
Indicates that something serves as the usual or characteristic function or role of an entity.
-
E.
standardExample
Indicates that something is a typical or canonical instance used to illustrate a general case or concept.
- 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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6318e4c9c8190960df19eed7546fa |
completed | May 2, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:25 p.m.