Triple
T28051115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunn effect |
E708821
|
entity |
| Predicate | hasTypicalFrequencyRange |
P44311
|
FINISHED |
| Object | from a few GHz to tens of GHz |
—
|
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: from a few GHz to tens of GHz | Statement: [Gunn effect, hasTypicalFrequencyRange, from a few GHz to tens of GHz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalFrequencyRange Context triple: [Gunn effect, hasTypicalFrequencyRange, from a few GHz to tens of GHz]
-
A.
hasFrequencyNote
Indicates that something is associated with a specific note describing how often it occurs or is repeated.
-
B.
soundFrequencyRange
Indicates the range of sound frequencies within which the related entity operates, is effective, or is characterized.
-
C.
hasBandRange
chosen
Indicates that one entity has an associated range or span of bands (such as frequency or wavelength intervals) defined by the other entity.
-
D.
hasMelodicRange
Indicates that a musical piece, phrase, or part spans a specific interval between its lowest and highest pitches.
-
E.
hasFrequencyCategory
Indicates that something is associated with a particular classification of how often it occurs or is used.
- 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_69ef9b6df9f48190bbb971d02cbe1b65 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: April 27, 2026, 8:33 p.m.