Triple
T531219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Electors |
E12225
|
entity |
| Predicate | numberOfElectors |
P16492
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [College of Electors, numberOfElectors, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfElectors Context triple: [College of Electors, numberOfElectors, 7]
-
A.
hasElectoralVotes
Indicates that a political entity (such as a state or district) possesses a specified number of votes in an electoral system used to choose an officeholder.
-
B.
electoralVotesWinner
Indicates that the subject is the candidate who received the highest number of electoral votes in a given election.
-
C.
electoralVotesNeededToWin
Indicates the minimum number of electoral votes a candidate must obtain in an election to be declared the winner.
-
D.
opponentElectoralVotes
Indicates the number of electoral votes received by the opposing candidate or party in an election.
-
E.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
- F. None of above. chosen
Provenance (4 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b257108190a537dffbb9d621b5 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a49857e1148190aa782b82675cf0b5 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.