Triple
T8808798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Councillor |
E209601
|
entity |
| Predicate | equivalentOfficeInItalian |
P48373
|
FINISHED |
| Object | Consigliere federale |
—
|
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: Consigliere federale | Statement: [Federal Councillor, equivalentOfficeInItalian, Consigliere federale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentOfficeInItalian Context triple: [Federal Councillor, equivalentOfficeInItalian, Consigliere federale]
-
A.
equivalentOffice
Indicates that two offices are considered functionally or formally the same position, role, or authority, even if they differ in name or jurisdiction.
-
B.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
C.
equivalentTitleInItalian
chosen
Indicates that one entity’s title is an equivalent version of another entity’s title expressed in Italian.
-
D.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
E.
comparableOffice
Indicates that two offices are sufficiently similar in relevant characteristics (such as size, function, or status) to be meaningfully compared to each other.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fd4cbec8190a929d4e60da8ad65 |
completed | March 31, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:45 p.m.