Triple
T19094346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch municipal elections |
E467365
|
entity |
| Predicate | hasVoterTurnoutTrend |
P19117
|
FINISHED |
| Object | generally lower than national parliamentary elections |
—
|
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: generally lower than national parliamentary elections | Statement: [Dutch municipal elections, hasVoterTurnoutTrend, generally lower than national parliamentary elections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVoterTurnoutTrend Context triple: [Dutch municipal elections, hasVoterTurnoutTrend, generally lower than national parliamentary elections]
-
A.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
B.
hasVoterRegistrationTendency
Indicates a tendency or likelihood for an entity to register (or be registered) as a voter.
-
C.
voterTurnoutDescription
chosen
Indicates a textual explanation or characterization of the level, nature, or patterns of voter turnout in an election or voting event.
-
D.
voterTurnoutPercentage
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
E.
turnoutVariesByYear
Indicates that the level of turnout changes depending on the specific year considered.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34e1ee0819092f679d916e6e532 |
completed | April 20, 2026, 8:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9a604308190a3235184f9f2c056 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.