Triple
T7194320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vandermonde's identity |
E167770
|
entity |
| Predicate | hasSymmetryProperty |
P60479
|
FINISHED |
| Object | symmetric in m and n |
—
|
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: symmetric in m and n | Statement: [Vandermonde's identity, hasSymmetryProperty, symmetric in m and n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymmetryProperty Context triple: [Vandermonde's identity, hasSymmetryProperty, symmetric in m and n]
-
A.
hasSymmetryType
chosen
Indicates that one entity possesses a specific kind or pattern of symmetry characterized or classified by the other entity.
-
B.
isSymmetric
Indicates that a relationship holds in both directions between two entities, so if it applies from A to B, it also applies from B to A.
-
C.
usesSymmetryGroup
Indicates that one entity employs or is based on a particular symmetry group in its structure, behavior, or formulation.
-
D.
isSymmetricAbout
Indicates that one entity is a mirror image of another with respect to a specified axis, point, or plane of symmetry.
-
E.
testsSymmetry
Indicates that one entity evaluates or verifies whether a relationship or property holds identically in both directions between two entities.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9050164819081fd6a11d10f9833 |
completed | March 27, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:50 p.m.