Triple
T6770355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1872 United States presidential election |
E155026
|
entity |
| Predicate | electoralVoteCountWinner |
P6366
|
FINISHED |
| Object | 286 |
—
|
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: 286 | Statement: [1872 United States presidential election, electoralVoteCountWinner, 286]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electoralVoteCountWinner Context triple: [1872 United States presidential election, electoralVoteCountWinner, 286]
-
A.
electoralVotesWinner
chosen
Indicates that the subject is the candidate who received the highest number of electoral votes in a given election.
-
B.
electoralVotesReceived
Indicates that one entity received a specified number of electoral votes in an election from another entity or jurisdiction.
-
C.
electoralVoteFor
Indicates that a specified number of electoral votes are allocated or cast in favor of a particular candidate or option in an election.
-
D.
electoralVoteOutcome
Indicates the result of an election in terms of how electoral votes are allocated or distributed among candidates or options.
-
E.
rankInElectoralCollege
Indicates the position or standing an entity holds within the ordering of members in an electoral college for a given election or 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2347fb48190a44c03317b5ecfd7 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.