Triple

T3345913
Position Surface form Disambiguated ID Type / Status
Subject 1852 United States presidential election E70373 entity
Predicate popularVoteMainOpponent P26912 FINISHED
Object 1314184 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: 1314184 | Statement: [1852 United States presidential election, popularVoteMainOpponent, 1314184]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: popularVoteMainOpponent
Context triple: [1852 United States presidential election, popularVoteMainOpponent, 1314184]
  • A. popularVoteWinner
    Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an election.
  • B. popularVoteRunnerUp
    Indicates that one entity is the candidate who received the second-highest number of votes in a popular vote for the other entity’s election or contest.
  • C. popularVoteLoser
    Indicates that the subject became the winner of an election despite receiving fewer popular votes than at least one opponent.
  • D. electionOpponent chosen
    Indicates that two individuals are rivals competing against each other in the same election.
  • E. popularVotes
    Indicates the number of votes an entity (such as a candidate or option) receives directly from individual voters in an election or decision process.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1f36c74819093ef2c74a46c2351 completed March 8, 2026, 5:29 p.m.
PD Predicate disambiguation batch_69ada42df1d48190874bb05f95deefde completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:12 p.m.