Triple
T6832821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss’s remarkable theorem |
E157378
|
entity |
| Predicate | typeOfCurvature |
P4461
|
FINISHED |
| Object | sectional curvature in dimension two |
—
|
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: sectional curvature in dimension two | Statement: [Gauss’s remarkable theorem, typeOfCurvature, sectional curvature in dimension two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCurvature Context triple: [Gauss’s remarkable theorem, typeOfCurvature, sectional curvature in dimension two]
-
A.
isCurved
Indicates that an object or path deviates smoothly from a straight line, forming a bend or arc.
-
B.
hasCurvatureInvariant
chosen
Indicates that one entity possesses a specific curvature-related invariant property or value associated with its geometric or mathematical structure.
-
C.
hasCurvatureDivergence
Indicates that one entity exhibits a difference or variation in curvature relative to another entity or reference.
-
D.
allowsSpatialCurvature
Indicates that one entity permits or enables the presence or variation of spatial curvature in relation to another entity or context.
-
E.
slopeType
Indicates the classification of a slope based on its geometric or physical characteristics, such as steepness, shape, or orientation.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:18 p.m.