Triple

T11750861
Position Surface form Disambiguated ID Type / Status
Subject 2018 Toronto mayoral election E279398 entity
Predicate percentageForJenniferKeesmaat P101144 FINISHED
Object 23.6 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: 23.6 | Statement: [2018 Toronto mayoral election, percentageForJenniferKeesmaat, 23.6]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: percentageForJenniferKeesmaat
Context triple: [2018 Toronto mayoral election, percentageForJenniferKeesmaat, 23.6]
  • A. positionInBelgianPolitics
    Indicates that an entity holds or has held an official role or office within the political system or institutions of Belgium.
  • B. voterTurnoutPercentage
    Indicates the proportion of eligible or registered voters who actually cast a ballot in a given election, expressed as a percentage.
  • C. oppositionPercentage
    Indicates the proportion of entities or participants that are in opposition to a given proposal, action, or subject relative to the whole.
  • D. rulingPartyPopularVotePercentage
    Indicates the percentage of the total popular vote received by the party currently in power or holding the ruling position.
  • E. eraRepresented
    Indicates that a subject depicts, symbolizes, or stands for a particular historical or temporal era.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a508b0c4819082fbcc27d559ea2f completed April 10, 2026, 7:21 a.m.
PD Predicate disambiguation batch_69d88a813cc48190a3dfdc60e8af80ae completed April 10, 2026, 5:28 a.m.
PDg Predicate description generation batch_69d890458d948190b15054c9ba0fd923 completed April 10, 2026, 5:53 a.m.
Created at: April 8, 2026, 9:41 p.m.