Triple
T22991646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sérgio Moro |
E572063
|
entity |
| Predicate | appointedBy |
P257
|
FINISHED |
| Object | Jair Bolsonaro |
—
|
NE NERFINISHED |
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: Jair Bolsonaro | Statement: [Sérgio Moro, appointedBy, Jair Bolsonaro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jair Bolsonaro Context triple: [Sérgio Moro, appointedBy, Jair Bolsonaro]
-
A.
Jair Bolsonaro
chosen
Jair Bolsonaro is a far-right Brazilian politician and former army captain who served as the 38th President of Brazil from 2019 to 2022.
-
B.
Michel Temer
Michel Temer is a Brazilian lawyer and politician who served as the 37th President of Brazil from 2016 to 2018 following the impeachment of Dilma Rousseff.
-
C.
Lula
Lula is a feminine given name, often used in English-speaking countries and sometimes as a diminutive of names like Louise or Tallulah.
-
D.
Pedro Rousseff
Pedro Rousseff is the son of former Brazilian president Dilma Rousseff.
-
E.
Jair
Jair is a minor biblical judge of Israel mentioned in the Book of Judges, known for his leadership and his thirty sons who rode thirty donkeys and controlled thirty towns.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182eefd688190853977421540b2ce |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.