Triple
T25725500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon–Hartley theorem |
E645105
|
entity |
| Predicate | unitOfCapacity |
P159021
|
FINISHED |
| Object | bits per second |
—
|
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: bits per second | Statement: [Shannon–Hartley theorem, unitOfCapacity, bits per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unitOfCapacity Context triple: [Shannon–Hartley theorem, unitOfCapacity, bits per second]
-
A.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
B.
storageCapacity
Indicates the maximum amount of data or material that a storage entity can hold.
-
C.
reservoirCapacityUnit
Indicates the unit of measurement used to express the capacity of a reservoir.
-
D.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
E.
installedCapacityUnit
Indicates the unit of measurement used to express the installed capacity associated with an entity.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcb6562481909de5461493ab10b1 |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 10:23 p.m.