Triple
T33419073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Busemann function |
E855796
|
entity |
| Predicate | wellDefinedUpTo |
P147762
|
FINISHED |
| Object | additive constant |
—
|
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: additive constant | Statement: [Busemann function, wellDefinedUpTo, additive constant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wellDefinedUpTo Context triple: [Busemann function, wellDefinedUpTo, additive constant]
-
A.
uniquenessUpTo
chosen
Indicates that two entities are considered essentially the same because they differ, at most, by a specified equivalence or transformation.
-
B.
wellPosedness
Indicates that a problem or system satisfies the conditions (such as existence, uniqueness, and stability of solutions) required to be considered mathematically well-posed.
-
C.
isAssociativeUpToIsomorphism
Indicates that a binary operation is associative in a structural sense, meaning any two ways of parenthesizing a finite product are related by a canonical isomorphism rather than strict equality.
-
D.
wasDefinedBy
Indicates that something was formally specified, described, or established by a particular agent, source, or defining entity.
-
E.
defined
Indicates that one entity specifies, explains, or establishes the meaning, scope, or identity of another entity.
- 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_69f3496fdf0081908c1aa30870ce518b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e47f37848190aadb137c81760f1f |
completed | May 3, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:36 a.m.