Triple
T1022659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Specific Area Message Encoding |
E22072
|
entity |
| Predicate | usesFrequency |
P23478
|
FINISHED |
| Object | 520.83 baud mark and space tones |
—
|
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: 520.83 baud mark and space tones | Statement: [Specific Area Message Encoding, usesFrequency, 520.83 baud mark and space tones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFrequency Context triple: [Specific Area Message Encoding, usesFrequency, 520.83 baud mark and space tones]
-
A.
frequency
Indicates how often an event, action, or relationship occurs within a given period or context.
-
B.
frequencyDependsOn
Indicates that the frequency of one event, action, or state is determined or influenced by another factor or condition.
-
C.
hasFrequencyNote
Indicates that something is associated with a specific note describing how often it occurs or is repeated.
-
D.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
E.
frequencyComparedTo
Indicates how often one event or action occurs relative to another, expressing a comparison of their frequencies.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e0f8908190bfe0a4cd8b31dfed |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b72619cc8190932fdfa0c74dc055 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7a0d0308190a00192aa9062bdaa |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.