Triple
T11205515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yang monopole |
E265148
|
entity |
| Predicate | dimensionOfConfigurationSpace |
P97850
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Yang monopole, dimensionOfConfigurationSpace, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOfConfigurationSpace Context triple: [Yang monopole, dimensionOfConfigurationSpace, 4]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
C.
dimensionOfComponents
Indicates that a specified dimension value is associated with, or applies to, the components of an object or system.
-
D.
dimensionVector
Indicates a vector that specifies the magnitudes or extents of an entity along multiple dimensions or measurement axes.
-
E.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d4eef88190a7f05bca82d919b9 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.