Triple
T4117403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2012 United States presidential election |
E90325
|
entity |
| Predicate | voterTurnoutApproximate |
P1234
|
FINISHED |
| Object | 57.5% |
—
|
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: 57.5% | Statement: [2012 United States presidential election, voterTurnoutApproximate, 57.5%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voterTurnoutApproximate Context triple: [2012 United States presidential election, voterTurnoutApproximate, 57.5%]
-
A.
voterTurnoutPercentage
chosen
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
B.
approximateNumberOfVotersBefore
Indicates that one value represents an estimated count of voters that existed prior to a specified point in time or event.
-
C.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
D.
voterTurnoutDescription
Indicates a textual explanation or characterization of the level, nature, or patterns of voter turnout in an election or voting event.
-
E.
typicalPresidentialVote
Indicates that the vote cast aligns with the usual or characteristic voting pattern observed in presidential elections.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:41 p.m.