Triple
T33660526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rankine cycle |
E862337
|
entity |
| Predicate | hasEfficiencyMetric |
P177821
|
FINISHED |
| Object | thermal efficiency |
—
|
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: thermal efficiency | Statement: [Rankine cycle, hasEfficiencyMetric, thermal efficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEfficiencyMetric Context triple: [Rankine cycle, hasEfficiencyMetric, thermal efficiency]
-
A.
sampleEfficiency
Indicates how effectively a method or system learns or performs using a limited number of samples or data points.
-
B.
hasMaximumEfficiencyAt
Indicates that an entity reaches or exhibits its highest possible efficiency under a specified condition, context, or parameter value.
-
C.
maximumEfficiency
Indicates that an entity operates at its highest possible level of performance or productivity under given conditions.
-
D.
energyEfficiencyFeature
Indicates that an entity has a design, technology, or characteristic specifically intended to reduce energy consumption or improve energy performance.
-
E.
isResourceEfficient
Indicates that an entity uses resources (such as energy, materials, or time) in a way that minimizes waste and maximizes effectiveness.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f70519f114819080659840c04d7911 |
completed | May 3, 2026, 8:19 a.m. |
Created at: May 1, 2026, 1:42 a.m.