Triple
T25725501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shannon–Hartley theorem |
E645105
|
entity |
| Predicate | bandwidthUnit |
P159022
|
FINISHED |
| Object | hertz |
—
|
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: hertz | Statement: [Shannon–Hartley theorem, bandwidthUnit, hertz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bandwidthUnit Context triple: [Shannon–Hartley theorem, bandwidthUnit, hertz]
-
A.
bandwidthClass
Indicates the classification of a connection or resource based on its available or allocated bandwidth capacity.
-
B.
bandwidthCharacteristic
Indicates the relationship specifying the bandwidth-related properties or constraints associated with a connection, link, or communication channel.
-
C.
dataRate
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
-
D.
supportsBandwidths
Indicates that an entity is compatible with or can operate using the specified range or set of bandwidth values.
-
E.
bandwidthEfficiency
Indicates how effectively available bandwidth is utilized to transmit data relative to capacity or resource usage.
- 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.