Triple

T8084060
Position Surface form Disambiguated ID Type / Status
Subject Sainte-Laguë method E188686 entity
Predicate usesDivisorSequenceType P80414 FINISHED
Object odd numbers 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: odd numbers | Statement: [Sainte-Laguë method, usesDivisorSequenceType, odd numbers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesDivisorSequenceType
Context triple: [Sainte-Laguë method, usesDivisorSequenceType, odd numbers]
  • A. usesDivisor
    Indicates that one entity employs another entity as a divisor in a division or modular arithmetic operation.
  • B. isDividedBy
    Indicates that one quantity or entity serves as the divisor that evenly or proportionally separates another quantity or entity into parts.
  • C. dividedBy
    Indicates that one quantity is separated into a specified number of equal parts or groups by another quantity, representing a division relationship between them.
  • D. isDivisible
    Indicates that one quantity can be evenly divided by another without leaving a remainder.
  • E. isDivisibleUnitOf
    Indicates that one unit can be evenly divided into another unit, such that the second unit is an exact multiple or fraction of the first.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb415e61ac81909e924aea69a7ff77 completed March 31, 2026, 3:37 a.m.
PD Predicate disambiguation batch_69cb04a14cd88190a79ed26cbeec1c33 completed March 30, 2026, 11:17 p.m.
PDg Predicate description generation batch_69cb14be17208190bb51c3dfcb613f20 completed March 31, 2026, 12:26 a.m.
Created at: March 30, 2026, 5:29 p.m.