Triple
T5538052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Principles of Statistical Mechanics |
E145215
|
entity |
| Predicate | subject |
P450
|
FINISHED |
| Object | Gibbs ensembles |
E284681
|
NE FINISHED |
How this triple was built (2 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: Gibbs ensembles | Statement: [The Principles of Statistical Mechanics, subject, Gibbs ensembles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gibbs ensembles Context triple: [The Principles of Statistical Mechanics, subject, Gibbs ensembles]
-
A.
Gibbs ensemble
chosen
The Gibbs ensemble is a statistical physics framework that describes the probabilistic distribution of microstates for systems in thermal equilibrium, typically at fixed temperature, volume, and particle number.
-
B.
Kirkwood approximation in statistical mechanics
The Kirkwood approximation in statistical mechanics is a method for approximating many-particle correlation functions by expressing higher-order correlations in terms of lower-order ones, simplifying the description of interacting particle systems.
-
C.
Computer experiments on classical fluids
"Computer experiments on classical fluids" is a pioneering work in computational physics that used numerical simulations to study the behavior and dynamics of classical fluid systems.
-
D.
Boltzmann–Gibbs entropy in statistical mechanics
Boltzmann–Gibbs entropy in statistical mechanics is the standard measure of disorder or uncertainty in a system, quantifying how many microscopic configurations correspond to a given macroscopic state and forming the basis of classical equilibrium statistical mechanics.
-
E.
Gibbs sampling
Gibbs sampling is a Markov chain Monte Carlo algorithm that generates samples from complex multivariate probability distributions by iteratively sampling each variable from its conditional distribution given the others.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fb19cb8819088b21e8ebef63d8b |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02817cb04819088df72950c791144 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:34 p.m.