Triple
T21442447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betamax |
E528969
|
entity |
| Predicate | signalToNoiseRatio |
P55008
|
FINISHED |
| Object | higher than VHS (contemporary models) |
—
|
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: higher than VHS (contemporary models) | Statement: [Betamax, signalToNoiseRatio, higher than VHS (contemporary models)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signalToNoiseRatio Context triple: [Betamax, signalToNoiseRatio, higher than VHS (contemporary models)]
-
A.
signalLevel
Indicates the intensity or strength of a transmitted or received signal in a communication context.
-
B.
signalTool
Indicates that one entity uses or activates a tool or mechanism to send a signal or convey information to another entity or system.
-
C.
noiseFigureRange
Indicates the range of acceptable or observed noise figure values associated with a system, component, or link in a given context.
-
D.
signalProperty
chosen
Indicates that one entity has a specific characteristic, attribute, or feature related to a signal.
-
E.
representationRatio
Indicates the proportional relationship between how much one entity represents, depicts, or stands in for another relative to some whole or reference amount.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b70322bc8190ae693163ededf5a0 |
completed | April 22, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:05 p.m.