Triple
T18203479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Bohm |
E435847
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Bohm diffusion |
—
|
NE NERFINISHED |
How this triple was built (3 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: Bohm diffusion | Statement: [David Bohm, knownFor, Bohm diffusion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bohm diffusion Context triple: [David Bohm, knownFor, Bohm diffusion]
-
A.
Boltzmann–BGK equation
The Boltzmann–BGK equation is a simplified kinetic model that replaces the complex collision term of the Boltzmann equation with a single relaxation-time approximation to describe gas particle dynamics.
-
B.
Kapitza–Dirac effect
The Kapitza–Dirac effect is a quantum phenomenon in which a beam of particles, such as electrons or atoms, is diffracted by a standing wave of light, demonstrating the wave-particle duality of matter.
-
C.
Landau–Pomeranchuk–Migdal effect
The Landau–Pomeranchuk–Migdal effect is a quantum electrodynamics phenomenon in which high-energy electrons and photons in dense media experience suppressed bremsstrahlung and pair production due to multiple scattering.
-
D.
Fokker–Planck equation
The Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of a stochastic (random) process, such as Brownian motion.
-
E.
Boltzmann equation
The Boltzmann equation is a fundamental kinetic theory equation that describes the statistical behavior and time evolution of a dilute gas or particle distribution in phase space due to streaming and collisions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bohm diffusion Target entity description: Bohm diffusion is an anomalous plasma transport process characterized by a diffusion rate much higher than classical predictions, often scaling inversely with magnetic field strength.
-
A.
Boltzmann–BGK equation
The Boltzmann–BGK equation is a simplified kinetic model that replaces the complex collision term of the Boltzmann equation with a single relaxation-time approximation to describe gas particle dynamics.
-
B.
Kapitza–Dirac effect
The Kapitza–Dirac effect is a quantum phenomenon in which a beam of particles, such as electrons or atoms, is diffracted by a standing wave of light, demonstrating the wave-particle duality of matter.
-
C.
Landau–Pomeranchuk–Migdal effect
The Landau–Pomeranchuk–Migdal effect is a quantum electrodynamics phenomenon in which high-energy electrons and photons in dense media experience suppressed bremsstrahlung and pair production due to multiple scattering.
-
D.
Fokker–Planck equation
The Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of a stochastic (random) process, such as Brownian motion.
-
E.
Boltzmann equation
The Boltzmann equation is a fundamental kinetic theory equation that describes the statistical behavior and time evolution of a dilute gas or particle distribution in phase space due to streaming and collisions.
- F. None of above. chosen
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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e221bbbc819088a7559a46b7d4e7 |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.