Triple
T22729155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul J. Flory |
E562082
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Flory–Fox equation |
—
|
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: Flory–Fox equation | Statement: [Paul J. Flory, notableWork, Flory–Fox equation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flory–Fox equation Context triple: [Paul J. Flory, notableWork, Flory–Fox equation]
-
A.
Flory–Huggins solution theory
Flory–Huggins solution theory is a thermodynamic model that describes the mixing behavior and phase separation of polymer solutions by accounting for the size difference between polymer chains and solvent molecules.
-
B.
Carothers equation
The Carothers equation is a fundamental relation in polymer chemistry that links the average degree of polymerization to the extent of reaction in step-growth polymerizations.
-
C.
Ornstein–Zernike equation
The Ornstein–Zernike equation is a fundamental relation in statistical mechanics that links the total and direct correlation functions of a fluid, forming the basis for many liquid-state theories and approximations.
-
D.
Anderson–Schulz–Flory distribution
The Anderson–Schulz–Flory distribution is a statistical model that predicts the chain-length distribution of hydrocarbons formed during polymerization-type reactions such as the Fischer–Tropsch synthesis.
-
E.
Gibbs–Duhem equation
The Gibbs–Duhem equation is a fundamental thermodynamic relation that links changes in chemical potential, temperature, and pressure for multicomponent systems, ensuring consistency among intensive variables.
- 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: Flory–Fox equation Target entity description: The Flory–Fox equation is a fundamental polymer science relation that connects the glass transition temperature of a polymer to its molecular weight.
-
A.
Flory–Huggins solution theory
Flory–Huggins solution theory is a thermodynamic model that describes the mixing behavior and phase separation of polymer solutions by accounting for the size difference between polymer chains and solvent molecules.
-
B.
Carothers equation
The Carothers equation is a fundamental relation in polymer chemistry that links the average degree of polymerization to the extent of reaction in step-growth polymerizations.
-
C.
Ornstein–Zernike equation
The Ornstein–Zernike equation is a fundamental relation in statistical mechanics that links the total and direct correlation functions of a fluid, forming the basis for many liquid-state theories and approximations.
-
D.
Anderson–Schulz–Flory distribution
The Anderson–Schulz–Flory distribution is a statistical model that predicts the chain-length distribution of hydrocarbons formed during polymerization-type reactions such as the Fischer–Tropsch synthesis.
-
E.
Gibbs–Duhem equation
The Gibbs–Duhem equation is a fundamental thermodynamic relation that links changes in chemical potential, temperature, and pressure for multicomponent systems, ensuring consistency among intensive variables.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792be7d88190b6d7d79041fcba25 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:21 p.m.