Triple
T21059737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1788–89 United States presidential election |
E518818
|
entity |
| Predicate | electoralVotesForEdwardTelfair |
P46276
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [1788–89 United States presidential election, electoralVotesForEdwardTelfair, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electoralVotesForEdwardTelfair Context triple: [1788–89 United States presidential election, electoralVotesForEdwardTelfair, 1]
-
A.
electoralVoteFor
chosen
Indicates that a specified number of electoral votes are allocated or cast in favor of a particular candidate or option in an election.
-
B.
electoralVotesReceived
Indicates that one entity received a specified number of electoral votes in an election from another entity or jurisdiction.
-
C.
electoralVotesWinner
Indicates that the subject is the candidate who received the highest number of electoral votes in a given election.
-
D.
numberOfElectors
Indicates the total count of electors associated with a given entity or context.
-
E.
StephenADouglasElectoralVotes
Indicates the number of electoral votes received by Stephen A. Douglas in a given election or electoral contest.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd842e8881909f4ffc4c43b7fa9f |
completed | April 21, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:37 p.m.