Triple
T12070052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dulong–Petit law for molar heat capacity of many solids at high temperature |
E287399
|
entity |
| Predicate | molarHeatCapacityValue |
P103039
|
FINISHED |
| Object | 3R |
—
|
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: 3R | Statement: [Dulong–Petit law for molar heat capacity of many solids at high temperature, molarHeatCapacityValue, 3R]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: molarHeatCapacityValue Context triple: [Dulong–Petit law for molar heat capacity of many solids at high temperature, molarHeatCapacityValue, 3R]
-
A.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
B.
thermalExpansionCoefficient
Indicates how much a material's size changes per unit length (or volume) for each degree change in temperature.
-
C.
thermalConductivity
Indicates how effectively heat is conducted through a material per unit temperature gradient.
-
D.
hasOrderOfMagnitudeInJoules
Indicates that the quantity associated with an entity is approximately of a specified order of magnitude when measured in joules.
-
E.
thermalCapacityPerReactor_MWth
Indicates the amount of thermal power capacity, measured in megawatts thermal (MWth), associated with each individual reactor.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:48 p.m.