Triple

T65239
Position Surface form Disambiguated ID Type / Status
Subject Born–Oppenheimer approximation E1297 entity
Predicate hasRefinement P4448 FINISHED
Object Born–Huang expansion
The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
E4701 NE FINISHED

How this triple was built (5 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: Born–Huang expansion | Statement: [Born–Oppenheimer approximation, hasRefinement, Born–Huang expansion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Born–Huang expansion
Context triple: [Born–Oppenheimer approximation, hasRefinement, Born–Huang expansion]
  • A. Born–Oppenheimer approximation
    The Born–Oppenheimer approximation is a fundamental method in molecular quantum mechanics that simplifies calculations by treating nuclear motion as much slower than electronic motion, allowing their behaviors to be separated.
  • B. Feynman–Kac formula
    The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
  • C. Feynman–Hellmann theorem
    The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
  • D. Feynman checkerboard model
    The Feynman checkerboard model is a path-integral-based lattice model introduced by Richard Feynman to illustrate and derive the behavior of relativistic quantum particles, particularly the Dirac equation in one spatial dimension.
  • E. Bose–Einstein statistics
    Bose–Einstein statistics is a quantum statistical framework that describes the distribution and collective behavior of indistinguishable bosons, underpinning phenomena such as Bose–Einstein condensation.
  • 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: Born–Huang expansion
Triple: [Born–Oppenheimer approximation, hasRefinement, Born–Huang expansion]
Generated description
The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Born–Huang expansion
Target entity description: The Born–Huang expansion is a quantum mechanical method that systematically improves upon the Born–Oppenheimer approximation by including couplings between electronic and nuclear motions in molecular systems.
  • A. Born–Oppenheimer approximation
    The Born–Oppenheimer approximation is a fundamental method in molecular quantum mechanics that simplifies calculations by treating nuclear motion as much slower than electronic motion, allowing their behaviors to be separated.
  • B. Feynman–Kac formula
    The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
  • C. Feynman–Hellmann theorem
    The Feynman–Hellmann theorem is a result in quantum mechanics that relates the derivative of an energy eigenvalue with respect to a parameter in the Hamiltonian to the expectation value of the corresponding derivative of the Hamiltonian.
  • D. Feynman checkerboard model
    The Feynman checkerboard model is a path-integral-based lattice model introduced by Richard Feynman to illustrate and derive the behavior of relativistic quantum particles, particularly the Dirac equation in one spatial dimension.
  • E. Bose–Einstein statistics
    Bose–Einstein statistics is a quantum statistical framework that describes the distribution and collective behavior of indistinguishable bosons, underpinning phenomena such as Bose–Einstein condensation.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRefinement
Context triple: [Born–Oppenheimer approximation, hasRefinement, Born–Huang expansion]
  • A. hasVariant
    Indicates that one entity exists as an alternative form, version, or variation of another entity.
  • B. hasCondition
    Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
  • C. hasLimitation
    Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
  • D. hasCurrent
    Indicates that an entity presently possesses, exhibits, or is associated with a particular state, attribute, or resource at the current time.
  • E. hasTerm
    Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
  • F. None of above. chosen

Provenance (7 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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a2516eda54819090f5c14384d4eab1 completed Feb. 28, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2554da8848190a445b503d98769aa completed Feb. 28, 2026, 2:39 a.m.
NEDg Description generation batch_69a255b409a081908871ed7fee07be29 completed Feb. 28, 2026, 2:40 a.m.
NED2 Entity disambiguation (via description) batch_69a256e8f7ec81909450c07bf7bafa0a completed Feb. 28, 2026, 2:46 a.m.
PD Predicate disambiguation batch_69a24ea5c140819080409a968c8d2ce8 completed Feb. 28, 2026, 2:10 a.m.
PDg Predicate description generation batch_69a2516d98e88190b79261bd3fcadd9b completed Feb. 28, 2026, 2:22 a.m.
Created at: Feb. 28, 2026, 2:02 a.m.