Triple

T18785570
Position Surface form Disambiguated ID Type / Status
Subject Gustav Magnus E459364 entity
Predicate knownFor P22 FINISHED
Object Magnus effect NE NERFINISHED

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: Magnus effect | Statement: [Gustav Magnus, knownFor, Magnus effect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magnus effect
Context triple: [Gustav Magnus, knownFor, Magnus effect]
  • A. Magnus effect chosen
    The Magnus effect is a physical phenomenon in which a spinning object moving through a fluid experiences a sideways force, causing its trajectory to curve.
  • B. Coriolis effect
    The Coriolis effect is the apparent deflection of moving objects caused by Earth's rotation, strongly influencing global wind patterns and ocean currents.
  • C. Saffman lift force
    The Saffman lift force is a hydrodynamic force acting on small particles in shear flow, causing them to migrate laterally due to velocity gradients in the surrounding fluid.
  • D. Kármán vortex street
    Kármán vortex street is a repeating pattern of swirling vortices formed when a fluid flows past a bluff body, fundamental in fluid dynamics and aerodynamics.
  • E. Saffman
    Saffman is a surname most notably associated with Philip G. Saffman, a prominent British-American applied mathematician and fluid dynamicist.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d396f54c8190ba49db31e8743842 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5978154ac819096356d2a488b45f0 completed April 20, 2026, 3:03 a.m.
Created at: April 10, 2026, 11:52 a.m.