Triple

T10966781
Position Surface form Disambiguated ID Type / Status
Subject 1920 United States presidential election E259120 entity
Predicate popularVoteForLoser P40073 FINISHED
Object 9,147,353 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: 9,147,353 | Statement: [1920 United States presidential election, popularVoteForLoser, 9,147,353]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: popularVoteForLoser
Context triple: [1920 United States presidential election, popularVoteForLoser, 9,147,353]
  • A. popularVoteLoser
    Indicates that the subject became the winner of an election despite receiving fewer popular votes than at least one opponent.
  • B. hasPopularVoteForLoser
    Indicates that in a given election, the candidate who lost the overall contest nonetheless received the majority of the popular vote.
  • C. popularVoteLoserTotal chosen
    Indicates that the subject is the candidate who lost the election overall but received the specified total number of popular votes.
  • D. popularVoteLoserParty
    Indicates that the subject is the political party of a candidate who lost the popular vote in an election.
  • E. popularVoteOutcome
    Indicates the result of a popular vote, specifying which option or candidate received the majority or winning share of votes.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7714ab8588190874289f84a132fe1 completed April 9, 2026, 9:28 a.m.
PD Predicate disambiguation batch_69d72e8c27cc81908050590b7a04cafd completed April 9, 2026, 4:43 a.m.
Created at: April 8, 2026, 9:24 p.m.