Triple
T5877556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwinger model |
E130663
|
entity |
| Predicate | hasSpacetimeDimension |
P3642
|
FINISHED |
| Object | 1+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: 1+1 | Statement: [Schwinger model, hasSpacetimeDimension, 1+1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpacetimeDimension Context triple: [Schwinger model, hasSpacetimeDimension, 1+1]
-
A.
spacetimeDimensionAssumed
chosen
Indicates that a specific number of spacetime dimensions is being taken as an assumption or working premise in a given context or model.
-
B.
hasDimensionality
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
C.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
D.
hasSpacetimeRegion
Indicates that something occupies, is associated with, or is bounded by a specific region in spacetime.
-
E.
hasIndividualDimension
Indicates that an entity possesses a specific, separately identifiable dimension or measurable extent as an individual attribute.
- 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_69c0085523688190bfd487479ce819e6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:57 p.m.