Triple

T25979685
Position Surface form Disambiguated ID Type / Status
Subject Pauli–Lubanski pseudovector E646032 entity
Predicate covarianceProperty P103048 FINISHED
Object Lorentz covariant 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: Lorentz covariant | Statement: [Pauli–Lubanski pseudovector, covarianceProperty, Lorentz covariant]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: covarianceProperty
Context triple: [Pauli–Lubanski pseudovector, covarianceProperty, Lorentz covariant]
  • A. hasCovarianceStructure
    Indicates that one entity possesses or is associated with a specific covariance structure that characterizes how its variables co-vary.
  • B. coefficientProperty
    Indicates a relationship where one entity serves as a coefficient or scalar factor that quantitatively modifies or characterizes another entity or property.
  • C. isGenerallyCovariant chosen
    Indicates that the form of the physical laws or equations remains unchanged under arbitrary smooth coordinate transformations (diffeomorphisms).
  • D. parityProperty
    Indicates that a relationship or quantity has a specific parity (such as being even, odd, or matching in parity) according to the defined property.
  • E. cumulativeProperty
    Indicates that a property of a whole is derived by aggregating or summing corresponding properties of its parts or components.
  • 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_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6050e507881909e3bc0c33e8a8c7e completed May 2, 2026, 2:07 p.m.
PD Predicate disambiguation batch_69f4a10480748190a2e67bd399fc435d completed May 1, 2026, 12:48 p.m.
Created at: April 22, 2026, 8:54 a.m.