Triple
T26847699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brillouin scattering |
E675969
|
entity |
| Predicate | hasFrequencyShiftScale |
P69694
|
FINISHED |
| Object | gigahertz range |
—
|
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: gigahertz range | Statement: [Brillouin scattering, hasFrequencyShiftScale, gigahertz range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequencyShiftScale Context triple: [Brillouin scattering, hasFrequencyShiftScale, gigahertz range]
-
A.
frequencyShiftProperty
chosen
Indicates a relationship where one entity specifies or characterizes the amount or nature of a change in frequency experienced by another entity or signal.
-
B.
hasFrequencyChannels
Indicates that an entity is associated with, or operates over, one or more specific frequency channels.
-
C.
hasFrequencyCategory
Indicates that something is associated with a particular classification of how often it occurs or is used.
-
D.
hasCarrierFrequency
Indicates that an entity (such as a signal or transmission) is associated with a specific carrier frequency at which it is transmitted or modulated.
-
E.
hasRotationFrequency
Indicates that one entity possesses or is characterized by a specific rate at which it rotates over time.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 5:13 a.m.