Triple
T33579924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwartz–Bruhat space |
E860122
|
entity |
| Predicate | dualSpace |
P131886
|
FINISHED |
| Object | space of tempered distributions on the group |
—
|
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: space of tempered distributions on the group | Statement: [Schwartz–Bruhat space, dualSpace, space of tempered distributions on the group]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dualSpace Context triple: [Schwartz–Bruhat space, dualSpace, space of tempered distributions on the group]
-
A.
hasDualSpace
chosen
Indicates that one mathematical space is the dual space consisting of all linear functionals defined on another space.
-
B.
dualPair
Indicates that two entities form a dual pair, standing in a mathematically defined dual relationship where each is the dual counterpart of the other.
-
C.
dualisticContext
Indicates a relationship or situation in which two contrasting or opposing aspects, perspectives, or forces are simultaneously present and contextually relevant.
-
D.
nullSpace
Indicates that a vector lies in the null space of a linear transformation, meaning it is mapped to the zero vector by that transformation.
-
E.
dualUse
Indicates that something serves both civilian and military (or peaceful and non-peaceful) purposes simultaneously.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f76f757081909165948fdcb254c7 |
completed | May 3, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.