Triple
T4667918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heaviside step function |
E102892
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Dirac delta function |
E199880
|
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: Dirac delta function | Statement: [Heaviside step function, relatedTo, Dirac delta function]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dirac delta function Context triple: [Heaviside step function, relatedTo, Dirac delta function]
-
A.
Dirac delta function
chosen
The Dirac delta function is a mathematical construct used in physics and engineering to model an idealized point mass or point charge, being zero everywhere except at a single point where it is infinitely large yet integrates to one.
-
B.
Kronecker delta
The Kronecker delta is a function of two variables that equals 1 when the variables are equal and 0 otherwise, widely used in linear algebra, tensor calculus, and discrete mathematics to represent identity relations.
-
C.
Heaviside step function
The Heaviside step function is a discontinuous mathematical function that jumps from 0 to 1 at a specified point and is widely used to model switching behavior and sudden changes in systems, especially in engineering and signal processing.
-
D.
Du Bois-Reymond function
The Du Bois-Reymond function is a classic example of a continuous but nowhere differentiable function, illustrating pathological behavior in real analysis.
-
E.
Dirichlet conditions
Dirichlet conditions are a set of sufficient criteria on a function—such as piecewise continuity and having a finite number of extrema and discontinuities on an interval—that guarantee the convergence of its Fourier series representation.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd633ec8b08190bf8ffd4c3b946f61 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be39c275a88190a65ceb1586257d1e |
completed | March 21, 2026, 6:25 a.m. |
Created at: March 20, 2026, 1:15 p.m.