Triple

T241831
Position Surface form Disambiguated ID Type / Status
Subject John Kerry 2004 presidential campaign E4946 entity
Predicate popularVotes P9220 FINISHED
Object approximately 59,028,000 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: approximately 59,028,000 | Statement: [John Kerry 2004 presidential campaign, popularVotes, approximately 59,028,000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: popularVotes
Context triple: [John Kerry 2004 presidential campaign, popularVotes, approximately 59,028,000]
  • 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. smithPopularVote
    Indicates that Smith received a specified number or share of votes in a popular vote election or ballot.
  • C. popularVoteRole
    Indicates the role or capacity in which an entity participates in or is associated with a popular vote.
  • D. popularVoteLoser
    Indicates that the subject became the winner of an election despite receiving fewer popular votes than at least one opponent.
  • E. 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.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d35aa288190966b6e15af1525cb completed Feb. 28, 2026, 3:12 a.m.
PD Predicate disambiguation batch_69a25b60ad308190b12f119960a8bde7 completed Feb. 28, 2026, 3:05 a.m.
PDg Predicate description generation batch_69a25d3463648190ac716d7475378536 completed Feb. 28, 2026, 3:12 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.