Triple
T21133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electoral College |
E419
|
entity |
| Predicate | electorSelectionMethod |
P539
|
FINISHED |
| Object | state law |
—
|
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: state law | Statement: [Electoral College, electorSelectionMethod, state law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electorSelectionMethod Context triple: [Electoral College, electorSelectionMethod, state law]
-
A.
electionMethod
chosen
Indicates the process or system used to select a candidate or make a decision in an election.
-
B.
elects
Indicates that one entity selects or chooses another entity for a position, role, or office, typically through a formal voting process.
-
C.
electedCandidate
Indicates that a particular person has been chosen as the winner in an election for a given position or office.
-
D.
smithPopularVote
Indicates that Smith received a specified number or share of votes in a popular vote election or ballot.
-
E.
popularVoteWinner
Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.