Triple
T33985661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siegel–Walfisz theorem |
E871402
|
entity |
| Predicate | errorTermType |
P73079
|
FINISHED |
| Object | O(x exp(-c√(log x))) for some c > 0, uniformly in q up to (log x)^A |
—
|
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: O(x exp(-c√(log x))) for some c > 0, uniformly in q up to (log x)^A | Statement: [Siegel–Walfisz theorem, errorTermType, O(x exp(-c√(log x))) for some c > 0, uniformly in q up to (log x)^A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorTermType Context triple: [Siegel–Walfisz theorem, errorTermType, O(x exp(-c√(log x))) for some c > 0, uniformly in q up to (log x)^A]
-
A.
errorTerm
chosen
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.
-
B.
errorType
Indicates the specific category or kind of error associated with an event, action, or entity.
-
C.
errorTermOrder
Indicates the ordering or sequence in which error terms are arranged or considered relative to one another.
-
D.
errorTypePrefix
Indicates that one entity specifies a prefix used to categorize or identify the type of an error associated with another entity.
-
E.
termType
Indicates the classification or category of a term within a system, specifying what kind of term it is (e.g., type, role, or function) in relation to others.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.