Triple
T37691908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian legislative election 2019 |
E938827
|
entity |
| Predicate | voterTurnoutComparedTo2017 |
P1235
|
FINISHED |
| Object | increased |
—
|
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: increased | Statement: [Austrian legislative election 2019, voterTurnoutComparedTo2017, increased]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voterTurnoutComparedTo2017 Context triple: [Austrian legislative election 2019, voterTurnoutComparedTo2017, increased]
-
A.
voterTurnoutPercentage
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
B.
voterTurnoutChange
chosen
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
C.
voterTurnoutDescription
Indicates a textual explanation or characterization of the level, nature, or patterns of voter turnout in an election or voting event.
-
D.
electionResult2017
Indicates the outcome or status of an election that took place in the year 2017.
-
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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.