Triple

T65228
Position Surface form Disambiguated ID Type / Status
Subject Born–Oppenheimer approximation E1297 entity
Predicate usedIn P98 FINISHED
Object Franck–Condon principle
The Franck–Condon principle is a rule in molecular spectroscopy that explains the intensity distribution of vibronic transitions by assuming electronic transitions occur much faster than nuclear motion, making vertical transitions between vibrational states most probable.
E4700 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: Franck–Condon principle | Statement: [Born–Oppenheimer approximation, usedIn, Franck–Condon principle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franck–Condon principle
Context triple: [Born–Oppenheimer approximation, usedIn, Franck–Condon principle]
  • 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–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.
  • C. Einstein coefficients
    Einstein coefficients are parameters in quantum theory that quantify the probabilities of absorption, spontaneous emission, and stimulated emission of radiation by atoms or molecules.
  • D. The Nature of the Chemical Bond
    The Nature of the Chemical Bond is a landmark chemistry book by Linus Pauling that systematically explains chemical bonding using quantum mechanics and became one of the most influential scientific texts of the 20th century.
  • E. Huygens–Fresnel principle
    The Huygens–Fresnel principle is a fundamental concept in wave optics that explains how every point on a wavefront acts as a source of secondary wavelets whose interference determines the wave’s subsequent propagation and diffraction.
  • 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: Franck–Condon principle
Triple: [Born–Oppenheimer approximation, usedIn, Franck–Condon principle]
Generated description
The Franck–Condon principle is a rule in molecular spectroscopy that explains the intensity distribution of vibronic transitions by assuming electronic transitions occur much faster than nuclear motion, making vertical transitions between vibrational states most probable.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Franck–Condon principle
Target entity description: The Franck–Condon principle is a rule in molecular spectroscopy that explains the intensity distribution of vibronic transitions by assuming electronic transitions occur much faster than nuclear motion, making vertical transitions between vibrational states most probable.
  • 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–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.
  • C. Einstein coefficients
    Einstein coefficients are parameters in quantum theory that quantify the probabilities of absorption, spontaneous emission, and stimulated emission of radiation by atoms or molecules.
  • D. The Nature of the Chemical Bond
    The Nature of the Chemical Bond is a landmark chemistry book by Linus Pauling that systematically explains chemical bonding using quantum mechanics and became one of the most influential scientific texts of the 20th century.
  • E. Huygens–Fresnel principle
    The Huygens–Fresnel principle is a fundamental concept in wave optics that explains how every point on a wavefront acts as a source of secondary wavelets whose interference determines the wave’s subsequent propagation and diffraction.
  • F. None of above. chosen

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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a24ee6ba348190b00977285d74d8f5 completed Feb. 28, 2026, 2:11 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.
Created at: Feb. 28, 2026, 2:02 a.m.