Triple
T6833468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli lemniscate |
E157392
|
entity |
| Predicate | cartesianEquation |
P12675
|
FINISHED |
| Object | (x^2 + y^2)^2 = a^2(x^2 - y^2) |
—
|
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: (x^2 + y^2)^2 = a^2(x^2 - y^2) | Statement: [Bernoulli lemniscate, cartesianEquation, (x^2 + y^2)^2 = a^2(x^2 - y^2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cartesianEquation Context triple: [Bernoulli lemniscate, cartesianEquation, (x^2 + y^2)^2 = a^2(x^2 - y^2)]
-
A.
relatedCurve
Indicates that one curve is associated with or derived from another curve in a defined relational way.
-
B.
mathematicallyExpressedBy
chosen
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
-
C.
geometricInterpretation
Indicates a relationship where one entity provides or embodies a geometric meaning, representation, or visualization of another entity.
-
D.
coordinateFunction
Indicates a functional relationship that maps or translates one set of coordinates to another within a defined space or system.
-
E.
supportsEquations
Indicates that one entity provides the capability to handle, display, or work with mathematical equations for another entity or within a given context.
- 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.