Triple

T16432250
Position Surface form Disambiguated ID Type / Status
Subject Jahn–Teller effect E399095 entity
Predicate dynamicVariantInvolves P13845 FINISHED
Object rapid interconversion between equivalent distorted structures 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: rapid interconversion between equivalent distorted structures | Statement: [Jahn–Teller effect, dynamicVariantInvolves, rapid interconversion between equivalent distorted structures]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: dynamicVariantInvolves
Context triple: [Jahn–Teller effect, dynamicVariantInvolves, rapid interconversion between equivalent distorted structures]
  • A. affectsVariant
    Indicates that one entity has an influence or impact on a specific variant or version of another entity.
  • B. variant
    Indicates that one entity is an alternative form, version, or variation of another entity.
  • C. governsVariant
    Indicates a regulatory relationship where one entity controls, influences, or determines the behavior or state of a specific variant of another entity.
  • D. rulesVariantOf
    Indicates that one set of rules is a modified or alternative version derived from another set of rules.
  • E. hasVariability chosen
    Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32b9f2e8c81909c60b8fb78255e5f completed April 18, 2026, 6:58 a.m.
PD Predicate disambiguation batch_69e22701d2288190bf8676050758f172 completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:10 a.m.