Triple

T19531825
Position Surface form Disambiguated ID Type / Status
Subject Hamming window E488673 entity
Predicate comparedTo P278 FINISHED
Object Hann 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: Hann window | Statement: [Hamming window, comparedTo, Hann window]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hann window
Context triple: [Hamming window, comparedTo, Hann 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. Chebyshev filters
    Chebyshev filters are a class of analog and digital filters characterized by a steeper roll-off than Butterworth filters at the cost of ripple in either the passband (Type I) or stopband (Type II).
  • E. Butterworth filters
    Butterworth filters are a class of signal-processing filters designed to have an especially flat frequency response in the passband, making them widely used for smooth, ripple-free filtering in analog and digital systems.
  • 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.