Triple

T21136
Position Surface form Disambiguated ID Type / Status
Subject Electoral College E419 entity
Predicate totalElectors P280 FINISHED
Object 538 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: 538 | Statement: [Electoral College, totalElectors, 538]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: totalElectors
Context triple: [Electoral College, totalElectors, 538]
  • A. hasElectoralVotes chosen
    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. electoralVotesNeededToWin
    Indicates the minimum number of electoral votes a candidate must obtain in an election to be declared the winner.
  • C. electoralVoteRunnerUp
    Indicates that the subject is the candidate who received the second-highest number of electoral votes in a given election.
  • D. elects
    Indicates that one entity selects or chooses another entity for a position, role, or office, typically through a formal voting process.
  • E. electionNumber
    Indicates the specific ordinal or identifying number assigned to a particular election within a series or system of elections.
  • 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.