Triple
T17196277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermi 2 |
E417358
|
entity |
| Predicate | netCapacityFactor_high |
P126688
|
FINISHED |
| Object | over 90 percent in some years |
—
|
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: over 90 percent in some years | Statement: [Fermi 2, netCapacityFactor_high, over 90 percent in some years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: netCapacityFactor_high Context triple: [Fermi 2, netCapacityFactor_high, over 90 percent in some years]
-
A.
designedForHighCapacity
Indicates that something is intentionally created or configured to handle a large volume, load, or throughput.
-
B.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
C.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
D.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
E.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daab57c819093496cbdc7890f34 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e39c2fedb881908bfed2c3e5f2616a |
completed | April 18, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:38 a.m.