Triple
T4065741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMRTG |
E86318
|
entity |
| Predicate | energyConversionMethod |
P37195
|
FINISHED |
| Object | thermoelectric conversion |
—
|
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: thermoelectric conversion | Statement: [MMRTG, energyConversionMethod, thermoelectric conversion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyConversionMethod Context triple: [MMRTG, energyConversionMethod, thermoelectric conversion]
-
A.
powerConversionMethod
chosen
Indicates the method or process by which one form of power or energy is converted into another.
-
B.
outputEnergy
Indicates that an entity produces or releases a certain amount or form of energy as a result of its operation or behavior.
-
C.
energyType
Indicates the kind or category of energy associated with an entity or process.
-
D.
energyThroughputCategory
Indicates the classification of an entity based on the amount or level of energy it processes or transfers over a given period.
-
E.
methodOfConversion
Indicates the specific process or technique used to transform one form, state, or representation into another.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0bdea48190805a79515ee92709 |
completed | March 9, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69aef90438908190a005b08ba271eacf |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.