Triple
T2373410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boltzmann distribution |
E46139
|
entity |
| Predicate | temperatureEffect |
P37402
|
FINISHED |
| Object | higher temperature increases population of higher energy states |
—
|
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: higher temperature increases population of higher energy states | Statement: [Boltzmann distribution, temperatureEffect, higher temperature increases population of higher energy states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temperatureEffect Context triple: [Boltzmann distribution, temperatureEffect, higher temperature increases population of higher energy states]
-
A.
temperatureDependent
chosen
Indicates that the existence, intensity, or outcome of a relationship or process varies as a function of temperature.
-
B.
temperatureProportionalTo
Indicates that the temperature of one entity changes in direct proportion to the temperature of another entity.
-
C.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
D.
temperatureControlMethod
Indicates the method or mechanism used to regulate or maintain a desired temperature.
-
E.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:56 p.m.