Triple

T9843608
Position Surface form Disambiguated ID Type / Status
Subject Cauchy–Riemann equations E239285 entity
Predicate regularityAssumption P90303 FINISHED
Object continuity of first partial derivatives 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: continuity of first partial derivatives | Statement: [Cauchy–Riemann equations, regularityAssumption, continuity of first partial derivatives]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regularityAssumption
Context triple: [Cauchy–Riemann equations, regularityAssumption, continuity of first partial derivatives]
  • A. hasRegularity
    Indicates that one entity exhibits a consistent, recurring pattern or uniform behavior with respect to another entity or over time.
  • B. regularityQuestion
    Indicates that one entity poses a question about the frequency, consistency, or regular occurrence of an event, action, or state involving another entity.
  • C. regularization
    Indicates the application of a constraint or penalty to a model or function to prevent overfitting and encourage simpler, more generalizable behavior.
  • D. areRegularIn
    Indicates that entities participate in or occur within a context, pattern, or structure in a consistent, uniform, and rule-governed manner.
  • E. regularizationControlledBy
    Indicates that the regularization applied in a process, model, or system is governed, adjusted, or determined by a specific controlling factor or mechanism.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb35c8e348190aa090c71bf6f30eb completed April 2, 2026, 12:07 a.m.
PD Predicate disambiguation batch_69cd03e57cac8190914bb5ae608a6e0e completed April 1, 2026, 11:39 a.m.
PDg Predicate description generation batch_69cd06ace53081909b5f81f382f6591e completed April 1, 2026, 11:51 a.m.
Created at: March 30, 2026, 8:33 p.m.