Triple

T11819507
Position Surface form Disambiguated ID Type / Status
Subject 2000 Russian presidential election E281086 entity
Predicate runnerUpVoteShare P9216 FINISHED
Object about 29.2% 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: about 29.2% | Statement: [2000 Russian presidential election, runnerUpVoteShare, about 29.2%]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: runnerUpVoteShare
Context triple: [2000 Russian presidential election, runnerUpVoteShare, about 29.2%]
  • A. secondRoundRunnerUpVoteSharePercentage
    Indicates the percentage of total votes received by the candidate who finished as runner-up in the second round of a contest or election.
  • B. runnerUp
    Indicates that one entity finished in second place relative to another in a competition or ranking.
  • C. 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.
  • D. popularVoteShare chosen
    Indicates the proportion of all votes cast in an election that were received by a particular candidate, party, or option.
  • E. runnerUpRank
    Indicates the position or ranking assigned to an entity that finishes immediately after the winner (or near the top) in a competition or ordered list.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e87e488190905bc3bb6d721e56 completed April 10, 2026, 7:25 a.m.
PD Predicate disambiguation batch_69d8a251fc08819095933f1d13c3b742 completed April 10, 2026, 7:10 a.m.
Created at: April 8, 2026, 9:42 p.m.