Triple
T10661688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levi-Civita symbol |
E251240
|
entity |
| Predicate | in3Dimensions |
P95204
|
FINISHED |
| Object | ε_{ijk} |
—
|
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: ε_{ijk} | Statement: [Levi-Civita symbol, in3Dimensions, ε_{ijk}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: in3Dimensions
Context triple: [Levi-Civita symbol, in3Dimensions, ε_{ijk}]
-
A.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
B.
has3DModels
Indicates that an entity is associated with one or more three-dimensional (3D) digital models representing it.
-
C.
has3DVersion
Indicates that an entity has a corresponding three-dimensional (3D) version or representation.
-
D.
includesDimension
Indicates that one entity encompasses or contains a particular dimension or measurable aspect as part of its definition or structure.
-
E.
dimensionOfCurrent
Indicates the dimensional property (such as magnitude or units) associated with the current in a given context.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e018d1e881909b8e62682104e842 |
completed | April 8, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69d6dd8753108190b799ffa0c760526e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:08 p.m.