Triple
T5978502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian elections |
E133059
|
entity |
| Predicate | presidentialReelectionLimit |
P10528
|
FINISHED |
| Object | 1 consecutive term |
—
|
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: 1 consecutive term | Statement: [Brazilian elections, presidentialReelectionLimit, 1 consecutive term]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presidentialReelectionLimit Context triple: [Brazilian elections, presidentialReelectionLimit, 1 consecutive term]
-
A.
allowsImmediatePresidentialReelection
chosen
Indicates that a system, rule, or provision permits a president to run for and assume a consecutive subsequent term without any intervening gap in office.
-
B.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
C.
reElectedToPresidency
Indicates that an individual, having previously served as president, is chosen again to hold the office of the presidency.
-
D.
inaugurationFrequency
Indicates how often inaugurations occur within a given time period or context.
-
E.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.