Triple

T5991898
Position Surface form Disambiguated ID Type / Status
Subject Svante Arrhenius E133368 entity
Predicate theory P450 FINISHED
Object Arrhenius equation for temperature dependence of reaction rates
The Arrhenius equation for temperature dependence of reaction rates is a fundamental formula in chemical kinetics that quantitatively relates a reaction’s rate constant to temperature and activation energy, explaining why reactions speed up as temperature increases.
E562310 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: Arrhenius equation for temperature dependence of reaction rates | Statement: [Svante Arrhenius, theory, Arrhenius equation for temperature dependence of reaction rates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arrhenius equation for temperature dependence of reaction rates
Context triple: [Svante Arrhenius, theory, Arrhenius equation for temperature dependence of reaction rates]
  • A. Butler–Volmer equation
    The Butler–Volmer equation is a fundamental relation in electrochemistry that describes how the rate of an electrode reaction (current density) depends on the electrode potential and reaction kinetics.
  • B. Fick's first law of diffusion
    Fick's first law of diffusion is a fundamental physical law that relates the diffusive flux of particles to the spatial gradient of their concentration, describing how substances move from regions of high to low concentration.
  • C. Saha ionization equation
    The Saha ionization equation is a fundamental formula in astrophysics and plasma physics that relates the ionization state of a gas in thermal equilibrium to its temperature and pressure, crucial for understanding stellar atmospheres and spectra.
  • D. Herzberg–Teller approximation
    The Herzberg–Teller approximation is a refinement in molecular spectroscopy that accounts for vibronic coupling by allowing electronic transition dipole moments to depend on nuclear coordinates, explaining intensity in otherwise forbidden transitions.
  • E. Clausius–Clapeyron relation
    The Clausius–Clapeyron relation is a fundamental thermodynamic equation that describes how the pressure and temperature of a phase transition, such as boiling or condensation, are related.
  • 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: Arrhenius equation for temperature dependence of reaction rates
Triple: [Svante Arrhenius, theory, Arrhenius equation for temperature dependence of reaction rates]
Generated description
The Arrhenius equation for temperature dependence of reaction rates is a fundamental formula in chemical kinetics that quantitatively relates a reaction’s rate constant to temperature and activation energy, explaining why reactions speed up as temperature increases.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arrhenius equation for temperature dependence of reaction rates
Target entity description: The Arrhenius equation for temperature dependence of reaction rates is a fundamental formula in chemical kinetics that quantitatively relates a reaction’s rate constant to temperature and activation energy, explaining why reactions speed up as temperature increases.
  • A. Butler–Volmer equation
    The Butler–Volmer equation is a fundamental relation in electrochemistry that describes how the rate of an electrode reaction (current density) depends on the electrode potential and reaction kinetics.
  • B. Fick's first law of diffusion
    Fick's first law of diffusion is a fundamental physical law that relates the diffusive flux of particles to the spatial gradient of their concentration, describing how substances move from regions of high to low concentration.
  • C. Saha ionization equation
    The Saha ionization equation is a fundamental formula in astrophysics and plasma physics that relates the ionization state of a gas in thermal equilibrium to its temperature and pressure, crucial for understanding stellar atmospheres and spectra.
  • D. Herzberg–Teller approximation
    The Herzberg–Teller approximation is a refinement in molecular spectroscopy that accounts for vibronic coupling by allowing electronic transition dipole moments to depend on nuclear coordinates, explaining intensity in otherwise forbidden transitions.
  • E. Clausius–Clapeyron relation
    The Clausius–Clapeyron relation is a fundamental thermodynamic equation that describes how the pressure and temperature of a phase transition, such as boiling or condensation, are related.
  • 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_69c0087010d081908bb8142342d63330 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04e8fd030819095a4f3b3d425ec21 completed March 22, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10861c0bc8190b6290d7363f4264a completed March 23, 2026, 9:31 a.m.
NEDg Description generation batch_69c10c44b6408190be8bc1d96e0db2e4 completed March 23, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69c10cd7c1c8819085ec8bee7f42afc4 completed March 23, 2026, 9:50 a.m.
Created at: March 22, 2026, 4:05 p.m.