Triple
T1535849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stefan–Boltzmann law |
E32546
|
entity |
| Predicate | emissivityRange |
P29594
|
FINISHED |
| Object | 0 to 1 |
—
|
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: 0 to 1 | Statement: [Stefan–Boltzmann law, emissivityRange, 0 to 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emissivityRange Context triple: [Stefan–Boltzmann law, emissivityRange, 0 to 1]
-
A.
surfaceTemperatureRange
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
B.
typicalEnergyRange
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
-
C.
operatingTemperature
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
D.
minSurfaceTemperature
Indicates the lowest temperature value observed or allowed on the surface of an object or environment.
-
E.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a915f1694081908f87b509eda1309f |
completed | March 5, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:26 p.m.