Triple
T26253258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | von Neumann neighborhood |
E656652
|
entity |
| Predicate | inHigherDimensionsHasCardinality |
P160412
|
FINISHED |
| Object | 2d (for dimension d, radius 1) |
—
|
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: 2d (for dimension d, radius 1) | Statement: [von Neumann neighborhood, inHigherDimensionsHasCardinality, 2d (for dimension d, radius 1)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inHigherDimensionsHasCardinality Context triple: [von Neumann neighborhood, inHigherDimensionsHasCardinality, 2d (for dimension d, radius 1)]
-
A.
hasDimensionality
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
B.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
C.
cardinality
Indicates the number of distinct elements or members in a given set or collection.
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
hasCardinal
Indicates that something possesses or is associated with a specific cardinal number or quantity.
- F. None of above. chosen
Provenance (4 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dcc29cc81908880bd825cb12141 |
completed | May 2, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f600be0de88190989611e952b03117 |
completed | May 2, 2026, 1:48 p.m. |
Created at: April 26, 2026, 9:07 p.m.