Triple

T529691
Position Surface form Disambiguated ID Type / Status
Subject Ginzburg–Landau theory of superconductivity E10997 entity
Predicate introduces P201 FINISHED
Object Ginzburg–Landau parameter
The Ginzburg–Landau parameter is a dimensionless quantity in superconductivity that characterizes the type of a superconductor by comparing its magnetic penetration depth to its coherence length.
E10997 NE FINISHED

How this triple was built (4 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: Ginzburg–Landau parameter | Statement: [Ginzburg–Landau theory of superconductivity, introduces, Ginzburg–Landau parameter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ginzburg–Landau parameter
Context triple: [Ginzburg–Landau theory of superconductivity, introduces, Ginzburg–Landau parameter]
  • A. Ginzburg–Landau theory of superconductivity
    The Ginzburg–Landau theory of superconductivity is a phenomenological framework that describes superconductors using a complex order parameter and macroscopic equations to capture phase transitions, coherence length, and magnetic behavior.
  • B. London equations
    The London equations are fundamental relations in superconductivity that describe how magnetic fields behave inside superconductors, capturing key features like the Meissner effect and zero electrical resistance.
  • C. Meissner effect
    The Meissner effect is the phenomenon in which a superconductor expels magnetic fields from its interior when cooled below its critical temperature, leading to perfect diamagnetism.
  • D. Abrikosov vortices
    Abrikosov vortices are quantized magnetic flux lines that penetrate type-II superconductors in a regular lattice when exposed to magnetic fields above a critical value.
  • E. de Haas–van Alphen effect
    The de Haas–van Alphen effect is a quantum oscillatory phenomenon in metals where the magnetization varies periodically with applied magnetic field, allowing precise mapping of the electronic structure and Fermi surface.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ginzburg–Landau parameter
Triple: [Ginzburg–Landau theory of superconductivity, introduces, Ginzburg–Landau parameter]
Generated description
The Ginzburg–Landau parameter is a dimensionless quantity in superconductivity that characterizes the type of a superconductor by comparing its magnetic penetration depth to its coherence length.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ginzburg–Landau parameter
Target entity description: The Ginzburg–Landau parameter is a dimensionless quantity in superconductivity that characterizes the type of a superconductor by comparing its magnetic penetration depth to its coherence length.
  • A. Ginzburg–Landau theory of superconductivity chosen
    The Ginzburg–Landau theory of superconductivity is a phenomenological framework that describes superconductors using a complex order parameter and macroscopic equations to capture phase transitions, coherence length, and magnetic behavior.
  • B. London equations
    The London equations are fundamental relations in superconductivity that describe how magnetic fields behave inside superconductors, capturing key features like the Meissner effect and zero electrical resistance.
  • C. Meissner effect
    The Meissner effect is the phenomenon in which a superconductor expels magnetic fields from its interior when cooled below its critical temperature, leading to perfect diamagnetism.
  • D. Abrikosov vortices
    Abrikosov vortices are quantized magnetic flux lines that penetrate type-II superconductors in a regular lattice when exposed to magnetic fields above a critical value.
  • E. de Haas–van Alphen effect
    The de Haas–van Alphen effect is a quantum oscillatory phenomenon in metals where the magnetization varies periodically with applied magnetic field, allowing precise mapping of the electronic structure and Fermi surface.
  • F. None of above.

Provenance (5 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_69a2e84b16c4819088d284c47c3a7968 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1d4984c8190ac372171b16bb5e4 completed Feb. 28, 2026, 1:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b5dabbe88190acf66bd30bc6312d completed March 1, 2026, 9:55 p.m.
NEDg Description generation batch_69a4b64487bc8190b879ddedc1585a04 completed March 1, 2026, 9:57 p.m.
NED2 Entity disambiguation (via description) batch_69a4b6ca3398819094bfbac0ba7a9c66 completed March 1, 2026, 9:59 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.