Triple
T14636279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water |
E343615
|
entity |
| Predicate | specificHeatCapacity |
P115140
|
FINISHED |
| Object | 4.18 J/(g·K) |
—
|
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: 4.18 J/(g·K) | Statement: [Water, specificHeatCapacity, 4.18 J/(g·K)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specificHeatCapacity Context triple: [Water, specificHeatCapacity, 4.18 J/(g·K)]
-
A.
molarHeatCapacityValue
Indicates the numerical value of the amount of heat required to raise the temperature of one mole of a substance by one degree under specified conditions.
-
B.
thermalProperty
Indicates a relationship where an entity is associated with a characteristic describing its behavior or response with respect to temperature or heat.
-
C.
thermalConductivity
Indicates how effectively heat is conducted through a material per unit temperature gradient.
-
D.
molarHeatCapacityApproximateNumericalValue
Indicates that an entity’s molar heat capacity is associated with a specific approximate numerical value.
-
E.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ab9578819085b4cf7244d30d87 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:26 a.m.