Triple
T1077300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UMTS |
E23867
|
entity |
| Predicate | usesModulation |
P23647
|
FINISHED |
| Object | 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: QPSK | Statement: [UMTS, usesModulation, QPSK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesModulation Context triple: [UMTS, usesModulation, QPSK]
-
A.
audioModulation
Indicates a relationship where one audio signal or parameter is used to vary or control another audio signal’s characteristics (such as amplitude, frequency, or timbre) over time.
-
B.
usesInstrument
Indicates that an agent performs an action by employing a specific instrument or tool as the means to carry it out.
-
C.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
D.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
E.
videoModulation
Indicates a relationship where one entity alters or controls the characteristics of a video signal or stream, such as its amplitude, frequency, or encoding parameters.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b94288d88190aae4fb86236c0702 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.