Triple
T12070074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dulong–Petit law for molar heat capacity of many solids at high temperature |
E287399
|
entity |
| Predicate | impliesPerAtomHeatCapacity |
P41476
|
FINISHED |
| Object | 3kB |
—
|
LITERAL 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: 3kB | Statement: [Dulong–Petit law for molar heat capacity of many solids at high temperature, impliesPerAtomHeatCapacity, 3kB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impliesPerAtomHeatCapacity Context triple: [Dulong–Petit law for molar heat capacity of many solids at high temperature, impliesPerAtomHeatCapacity, 3kB]
-
A.
energyPerDegreeOfFreedom
chosen
Indicates the amount of energy associated with each independent degree of freedom in a physical system.
-
B.
hasOrderOfMagnitudeInJoules
Indicates that the quantity associated with an entity is approximately of a specified order of magnitude when measured in joules.
-
C.
thermalExpansionCoefficient
Indicates how much a material's size changes per unit length (or volume) for each degree change in temperature.
-
D.
thermalConductivity
Indicates how effectively heat is conducted through a material per unit temperature gradient.
-
E.
temperatureDependenceExponent
Indicates how strongly a quantity or process changes in response to variations in temperature, typically expressed as an exponent in a temperature-dependent relationship.
- F. None of above.
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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.