Triple
T17723278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis turbine |
E442395
|
entity |
| Predicate | typicalEfficiency |
P98909
|
FINISHED |
| Object | high 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: high efficiency | Statement: [Francis turbine, typicalEfficiency, high efficiency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEfficiency Context triple: [Francis turbine, typicalEfficiency, high efficiency]
-
A.
typicalPowerConversionEfficiency
chosen
Indicates the usual or characteristic percentage of input power that is successfully converted to output power in a device or system.
-
B.
typicalEfficiencyComparedToPredecessor
Indicates how the usual or average efficiency of something compares to that of its predecessor.
-
C.
hasMaximumEfficiencyAt
Indicates that an entity reaches or exhibits its highest possible efficiency under a specified condition, context, or parameter value.
-
D.
thermalEfficiency
Indicates how effectively an energy conversion process transforms input energy into useful output work or heat, typically expressed as a ratio or percentage.
-
E.
typicalPower
Indicates the usual or characteristic amount of power associated with an entity under normal operating 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47487b4988190b14237a4e6376e9a |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:07 a.m.