Triple
T37184656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DVB-C2 |
E921290
|
entity |
| Predicate | usesModulationScheme |
P23647
|
FINISHED |
| Object | QAM |
—
|
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: QAM | Statement: [DVB-C2, usesModulationScheme, QAM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesModulationScheme Context triple: [DVB-C2, usesModulationScheme, QAM]
-
A.
usesModulation
chosen
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
-
B.
usesModality
Indicates that an action, communication, or process is carried out through or characterized by a particular modality (such as visual, auditory, tactile, or another mode of expression or operation).
-
C.
modulationCapabilities
Indicates the types or methods of signal modulation that an entity can perform or support.
-
D.
definesModulation
Indicates that one entity specifies or determines how another entity is modulated or altered in its behavior, intensity, or effect.
-
E.
usesCodec
Indicates that one entity employs or relies on a specific codec to encode, decode, or process data.
- 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_69f76ea250bc819083f28d81de25cd0c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: May 3, 2026, 4:15 p.m.