Triple
T179462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janet–Cartan theorem |
E3651
|
entity |
| Predicate | metricPreserved |
P4235
|
FINISHED |
| Object | Riemannian distance locally |
—
|
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: Riemannian distance locally | Statement: [Janet–Cartan theorem, metricPreserved, Riemannian distance locally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metricPreserved Context triple: [Janet–Cartan theorem, metricPreserved, Riemannian distance locally]
-
A.
invariantUnder
chosen
Indicates that a property, structure, or quantity remains unchanged when a specified transformation or operation is applied.
-
B.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
C.
hasCurvatureInvariant
Indicates that one entity possesses a specific curvature-related invariant property or value associated with its geometric or mathematical structure.
-
D.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
E.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.