Triple
T19531675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard W. Hamming |
E488670
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Hamming window |
—
|
NE NERFINISHED |
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: Hamming window | Statement: [Richard W. Hamming, knownFor, Hamming window]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamming window Context triple: [Richard W. Hamming, knownFor, Hamming window]
-
A.
Hamming window
chosen
The Hamming window is a mathematical function used in signal processing to reduce spectral leakage when analyzing finite-length signals with the Fourier transform.
-
B.
Haar wavelet
The Haar wavelet is the simplest and oldest wavelet function, used as a basic building block in wavelet analysis for representing signals with abrupt changes.
-
C.
Wiener filter
The Wiener filter is a signal processing technique that optimally estimates a desired signal from noisy observations by minimizing the mean square error, based on statistical properties of signal and noise.
-
D.
Walsh–Hadamard transform
The Walsh–Hadamard transform is an orthogonal, non-sinusoidal signal transform that decomposes data into a basis of square-wave-like functions, widely used in communications, coding theory, and signal processing.
-
E.
Gabor transform
The Gabor transform is a time–frequency analysis technique that represents signals using localized sinusoidal functions, enabling detailed examination of how a signal’s frequency content evolves over time.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6363fd1f8819080805346efad2579 |
completed | April 20, 2026, 2:20 p.m. |
Created at: April 10, 2026, 1:41 p.m.