Triple

T35332256
Position Surface form Disambiguated ID Type / Status
Subject Bloch wall E1020352 entity
Predicate hasApproximateThickness P169229 FINISHED
Object proportional to square root of exchange stiffness over anisotropy constant 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: proportional to square root of exchange stiffness over anisotropy constant | Statement: [Bloch wall, hasApproximateThickness, proportional to square root of exchange stiffness over anisotropy constant]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasApproximateThickness
Context triple: [Bloch wall, hasApproximateThickness, proportional to square root of exchange stiffness over anisotropy constant]
  • A. hasApproximateAverageThickness chosen
    Indicates that an entity possesses a thickness value that is an estimated or typical average rather than an exact measurement.
  • B. hasThicknessRange
    Indicates that an entity is associated with a minimum and maximum thickness value defining the range of its thickness.
  • C. hasMaximumThickness
    Indicates that an entity possesses a specified upper limit on its thickness.
  • D. hasDimensionsApprox
    Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
  • E. thickerThan
    Indicates that one entity has a greater thickness (is more thick) than 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_69f76deacf4481908e7735a5a7715b0a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fddd373cdc8190be1b12e70e4deb1f completed May 8, 2026, 12:55 p.m.
PD Predicate disambiguation batch_69fddc6915a88190ad41e379aa3ede13 completed May 8, 2026, 12:51 p.m.
Created at: May 3, 2026, 4:03 p.m.