Triple
T37420520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French presidential election of 1848 |
E929837
|
entity |
| Predicate | mainOpponentPopularVote |
P73183
|
FINISHED |
| Object | about 1,474,687 |
—
|
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 1,474,687 | Statement: [French presidential election of 1848, mainOpponentPopularVote, about 1,474,687]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainOpponentPopularVote Context triple: [French presidential election of 1848, mainOpponentPopularVote, about 1,474,687]
-
A.
popularVoteCountOpponent
chosen
Indicates the number of votes received by the opposing candidate or party in a popular vote contest.
-
B.
popularVoteOpponent
Indicates that one entity is the opponent of another in a popular vote or general election contest.
-
C.
opponentPopularVotePercentage
Indicates the percentage of the total popular vote received by the opposing candidate or party in an election.
-
D.
voteShareMainOpponent
Indicates the proportion of total votes received by the primary opposing candidate or party in an election.
-
E.
leader4PopularVote
Indicates that a leader holds their position as a result of receiving the highest number of votes in a popular election.
- 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_69f76ebf0f288190ba198a78341613b8 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:16 p.m.