Triple
T4693073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese elections |
E104078
|
entity |
| Predicate | presidentialElectionsFrequency |
P22629
|
FINISHED |
| Object | every 5 years |
—
|
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: every 5 years | Statement: [Portuguese elections, presidentialElectionsFrequency, every 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presidentialElectionsFrequency Context triple: [Portuguese elections, presidentialElectionsFrequency, every 5 years]
-
A.
inaugurationFrequency
Indicates how often inaugurations occur within a given time period or context.
-
B.
legislativePeriodicity
Indicates how frequently a legislative body or process recurs or is scheduled to occur over time.
-
C.
hasRegularElections
chosen
Indicates that a governing body or political entity holds elections at consistent, scheduled intervals according to established rules or norms.
-
D.
portionUpForElectionEachCycle
Indicates what fraction of the total membership or seats is contested in each election cycle.
-
E.
numberOfPresidentialCampaigns
Indicates the total count of times an individual has run as a candidate in a presidential election.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.