Triple
T1466970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French plebiscite of 1802 |
E27045
|
entity |
| Predicate | officialTurnout |
P1234
|
FINISHED |
| Object | about 49.45% |
—
|
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: about 49.45% | Statement: [French plebiscite of 1802, officialTurnout, about 49.45%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialTurnout Context triple: [French plebiscite of 1802, officialTurnout, about 49.45%]
-
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.
voterTurnoutChange
Indicates the amount or direction of change in voter turnout between two elections or time periods.
-
C.
electoralActivity
Indicates involvement in activities related to organizing, participating in, or influencing an election or electoral process.
-
D.
popularVotes
Indicates the number of votes an entity (such as a candidate or option) receives directly from individual voters in an election or decision process.
-
E.
voterTurnoutDescription
Indicates a textual explanation or characterization of the level, nature, or patterns of voter turnout in an election or voting event.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5bcfa0881909d6137c69825bc7a |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.