Triple

T5103121
Position Surface form Disambiguated ID Type / Status
Subject OFDM E115027 entity
Predicate uses P98 FINISHED
Object FFT E373658 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: FFT | Statement: [OFDM, uses, FFT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FFT
Context triple: [OFDM, uses, FFT]
  • A. FFT
    FFT is the ICAO airline designator used in aviation to identify Frontier Airlines in flight plans and air traffic control communications.
  • B. Fourier
    Fourier is a French surname most famously associated with Jean-Baptiste Joseph Fourier, the mathematician and physicist known for developing Fourier analysis and Fourier series.
  • C. Cooley–Tukey Fast Fourier Transform algorithm chosen
    The Cooley–Tukey Fast Fourier Transform algorithm is a widely used, efficient method for computing the discrete Fourier transform that revolutionized digital signal processing and numerical analysis.
  • D. Fourier analysis
    Fourier analysis is a mathematical method for decomposing functions or signals into sums of sinusoidal components, widely used in fields such as signal processing, physics, and engineering.
  • E. Fourier series
    A Fourier series is a way of representing a periodic function as an infinite sum of sines and cosines with appropriately chosen coefficients.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7586a4a08190866aea6be625837c completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba9106ec8190839a7de183efa359 completed March 21, 2026, 3:34 p.m.
Created at: March 20, 2026, 1:41 p.m.