Triple
T379070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricci curvature tensor |
E8635
|
entity |
| Predicate | dimensionOfComponents |
P12688
|
FINISHED |
| Object | n×n on an n-dimensional manifold |
—
|
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: n×n on an n-dimensional manifold | Statement: [Ricci curvature tensor, dimensionOfComponents, n×n on an n-dimensional manifold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dimensionOfComponents Context triple: [Ricci curvature tensor, dimensionOfComponents, n×n on an n-dimensional manifold]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
C.
dimensionType
Indicates the specific kind or category of dimension that characterizes how something is measured or structured.
-
D.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
E.
hasNationalDimension
Indicates that something possesses a scope, relevance, or impact at the level of a nation or entire country.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2974988190a1d6316cbb5159c8 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.