Triple

T11961269
Position Surface form Disambiguated ID Type / Status
Subject Fatou's lemma E284673 entity
Predicate inequalityType P35662 FINISHED
Object lower bound inequality 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: lower bound inequality | Statement: [Fatou's lemma, inequalityType, lower bound inequality]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: inequalityType
Context triple: [Fatou's lemma, inequalityType, lower bound inequality]
  • A. inequality
    Indicates that there is a difference or lack of equality in status, rights, opportunities, or treatment between entities.
  • B. equalityCondition
    Indicates that two values, expressions, or attributes must be exactly the same for the condition to be satisfied.
  • C. typeOfCondition chosen
    Indicates that one condition is a specific kind, category, or subtype of another condition.
  • D. invariantType
    Indicates that one entity has a type or classification that remains constant or unchanged under specified conditions or transformations.
  • E. dataProcessingInequality
    Indicates that processing data through a (possibly noisy) transformation cannot increase the information one variable has about another, so the mutual information between them can only stay the same or decrease.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9036941948190b150369094551731 completed April 10, 2026, 2:04 p.m.
PD Predicate disambiguation batch_69d8bb40f30c8190a0e0719bd67542bf completed April 10, 2026, 8:56 a.m.
Created at: April 8, 2026, 9:45 p.m.