Triple
T29100145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | π/4 DQPSK |
E736616
|
entity |
| Predicate | spectralEfficiency |
P127627
|
FINISHED |
| Object | similar to QPSK |
—
|
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: similar to QPSK | Statement: [π/4 DQPSK, spectralEfficiency, similar to QPSK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spectralEfficiency Context triple: [π/4 DQPSK, spectralEfficiency, similar to QPSK]
-
A.
bandwidthEfficiency
chosen
Indicates how effectively available bandwidth is utilized to transmit data relative to capacity or resource usage.
-
B.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
C.
spectralProperty
Indicates a relationship where an entity possesses or is characterized by a specific spectral feature, measurement, or behavior (e.g., in its frequency, wavelength, or energy spectrum).
-
D.
netEfficiency
Indicates the overall effectiveness of a system or process after accounting for all losses, typically expressed as the ratio of useful output to total input.
-
E.
spectralBandUse
Indicates how specific spectral bands are utilized or applied within a given context or process.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66184e9208190a66378cac527bca9 |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 11:11 a.m.