Triple
T25432868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirichlet approximation theorem |
E637303
|
entity |
| Predicate | errorBound |
P96513
|
FINISHED |
| Object | approximation error less than 1/q² for infinitely many rationals |
—
|
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: approximation error less than 1/q² for infinitely many rationals | Statement: [Dirichlet approximation theorem, errorBound, approximation error less than 1/q² for infinitely many rationals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorBound Context triple: [Dirichlet approximation theorem, errorBound, approximation error less than 1/q² for infinitely many rationals]
-
A.
boundedByApprox
Indicates that one quantity is constrained by another within an approximate or tolerance-based bound, rather than an exact strict limit.
-
B.
errorTerm
Indicates the specific discrepancy or residual value that quantifies the difference between an observed outcome and its predicted or true value in a model or calculation.
-
C.
errorSide
Indicates the side, party, or component on which an error occurs or is attributed in a given context.
-
D.
givesBoundOn
chosen
Indicates that one quantity provides an upper or lower limit (a bound) on the value or behavior of another quantity.
-
E.
errorReductionGoal
Indicates that an entity has a target or objective to decrease the number or rate of errors relative to a current or baseline level.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6dc7d088190b1e4c191172ea256 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:58 p.m.