Triple
T2081908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Bank of Brazil |
E45261
|
entity |
| Predicate | governorTermType |
P540
|
FINISHED |
| Object | fixed term (after autonomy law) |
—
|
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: fixed term (after autonomy law) | Statement: [Central Bank of Brazil, governorTermType, fixed term (after autonomy law)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governorTermType Context triple: [Central Bank of Brazil, governorTermType, fixed term (after autonomy law)]
-
A.
governorateType
Indicates the specific classification or category of a governorate within an administrative or governmental hierarchy.
-
B.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
-
C.
governorTitle
Indicates the official title or designation held by a person serving as a governor.
-
D.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
E.
numberOfTermsAsGovernor
Indicates the number of separate terms an individual has served in the role of governor.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba35c2588190933dba882f52dd17 |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b298a48190b4bdf7c9800b058d |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.