Triple

T11961415
Position Surface form Disambiguated ID Type / Status
Subject Tonelli's theorem E284676 entity
Predicate oftenPresentedWith P3100 FINISHED
Object Fubini's theorem in analysis textbooks 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: Fubini's theorem in analysis textbooks | Statement: [Tonelli's theorem, oftenPresentedWith, Fubini's theorem in analysis textbooks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oftenPresentedWith
Context triple: [Tonelli's theorem, oftenPresentedWith, Fubini's theorem in analysis textbooks]
  • A. oftenPresentedAs
    Indicates that one entity is frequently depicted, portrayed, or shown in the form or role of another entity.
  • B. commonlyIdentifiedWith
    Indicates that two entities are widely regarded or treated as the same or equivalent, even if they are formally distinct.
  • C. clinicalSignOf
    Indicates that one clinical sign is evidence or manifestation of a particular disease, condition, or underlying medical state.
  • D. manifestationsInclude
    Indicates that one entity’s manifestations or concrete expressions contain or encompass those of another entity.
  • E. oftenAccompaniedBy chosen
    Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
  • 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_69d9037848f481908276716675464464 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.