Triple
T25725927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hohenberg–Kohn theorem |
E645114
|
entity |
| Predicate | dimensionOfBasicVariable |
P123289
|
FINISHED |
| Object | three-dimensional spatial function |
—
|
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: three-dimensional spatial function | Statement: [Hohenberg–Kohn theorem, dimensionOfBasicVariable, three-dimensional spatial function]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOfBasicVariable Context triple: [Hohenberg–Kohn theorem, dimensionOfBasicVariable, three-dimensional spatial function]
-
A.
dimensionOfAmbientSpace
chosen
Indicates the dimensionality of the surrounding or embedding space in which an object or structure exists.
-
B.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
C.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
-
D.
boundaryDimension
Indicates the dimensionality of the boundary of an entity, such as whether its boundary is a point, line, surface, or higher-dimensional analogue.
-
E.
dimensionVector
Indicates a vector that specifies the magnitudes or extents of an entity along multiple dimensions or measurement axes.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcb7bc5c8190b3587f1f4dad9381 |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 10:28 p.m.