Triple
T1261851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SU(2)_L |
E12518
|
entity |
| Predicate | fundamentalRepresentationDimension |
P21740
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [SU(2)_L, fundamentalRepresentationDimension, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundamentalRepresentationDimension Context triple: [SU(2)_L, fundamentalRepresentationDimension, 2]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
dimensionOfSpinor
chosen
Indicates the numerical size (number of components) of a spinor representation associated with a given context or object.
-
C.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
D.
dimensionOfComponents
Indicates that a specified dimension value is associated with, or applies to, the components of an object or system.
-
E.
typicalRank
Indicates the usual or most common rank or position an entity holds within a given ordering or hierarchy.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.