Triple
T24805872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newton interpolation polynomial |
E620656
|
entity |
| Predicate | coefficientNotation |
P93936
|
FINISHED |
| Object | f[x_0, x_1, ..., x_k] |
—
|
LITERAL 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: f[x_0, x_1, ..., x_k] | Statement: [Newton interpolation polynomial, coefficientNotation, f[x_0, x_1, ..., x_k]]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coefficientNotation Context triple: [Newton interpolation polynomial, coefficientNotation, f[x_0, x_1, ..., x_k]]
-
A.
coefficientProperty
Indicates a relationship where one entity serves as a coefficient or scalar factor that quantitatively modifies or characterizes another entity or property.
-
B.
coefficientsIn
chosen
Indicates that one entity appears as a coefficient within the mathematical expression or representation of another entity.
-
C.
coefficientSystems
Indicates a relationship where specific numerical or algebraic coefficients are assigned or associated with a system, structure, or set of elements.
-
D.
offsetNotation
Indicates that one representation specifies how far and in what way another representation is shifted or displaced from a reference point or baseline.
-
E.
notation
Indicates a conventional way of symbolically representing or writing something, such as concepts, quantities, or operations, within a specific system.
- F. None of above.
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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 4:50 a.m.