Triple
T9787502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Pixel is Not a Little Square |
E237521
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Nyquist–Shannon sampling theorem |
E166675
|
NE 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: Nyquist–Shannon sampling theorem | Statement: [A Pixel is Not a Little Square, relatedTo, Nyquist–Shannon sampling theorem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyquist–Shannon sampling theorem Context triple: [A Pixel is Not a Little Square, relatedTo, Nyquist–Shannon sampling theorem]
-
A.
Nyquist theorem
chosen
The Nyquist theorem is a fundamental principle in signal processing that states a continuous signal can be perfectly reconstructed from its samples if it is sampled at more than twice its highest frequency component.
-
B.
Nyquist
Nyquist is a surname most famously associated with Swedish-American engineer Harry Nyquist, known for his foundational contributions to information theory and telecommunications.
-
C.
Wiener–Khinchin theorem
The Wiener–Khinchin theorem is a fundamental result in signal processing and probability theory that relates a wide-sense stationary random process’s autocorrelation function to its power spectral density via the Fourier transform.
-
D.
Parseval's theorem
Parseval's theorem is a fundamental result in Fourier analysis that equates the total energy of a function in the time (or spatial) domain with the total energy of its representation in the frequency domain.
-
E.
Shannon–Hartley theorem
The Shannon–Hartley theorem is a fundamental result in information theory that quantifies the maximum error-free data transmission rate over a communication channel with a given bandwidth and signal-to-noise ratio.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda211b0608190bc8ceb905d02db83 |
completed | April 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c427cb2c81909fce8e1958ab3282 |
completed | April 5, 2026, 2:08 a.m. |
Created at: March 30, 2026, 8:27 p.m.