Triple
T8356198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1856 United States presidential election |
E196686
|
entity |
| Predicate | turnoutEstimate |
P1234
|
FINISHED |
| Object | approximately 79.4% |
—
|
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: approximately 79.4% | Statement: [1856 United States presidential election, turnoutEstimate, approximately 79.4%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnoutEstimate Context triple: [1856 United States presidential election, turnoutEstimate, approximately 79.4%]
-
A.
turnout
Indicates the number or proportion of participants who attend or take part in an event or activity.
-
B.
voterTurnoutPercentage
chosen
Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
-
C.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
D.
approximateNumberOfVotersBefore
Indicates that one value represents an estimated count of voters that existed prior to a specified point in time or event.
-
E.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
- 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb804a344c819089c0a13fe66e3088 |
completed | March 31, 2026, 8:05 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.