Triple
T7420189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legendre symbol |
E171225
|
entity |
| Predicate | orthogonalityProperty |
P76852
|
FINISHED |
| Object | sum_{a mod p} (a/p)=0 |
—
|
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: sum_{a mod p} (a/p)=0 | Statement: [Legendre symbol, orthogonalityProperty, sum_{a mod p} (a/p)=0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthogonalityProperty
Context triple: [Legendre symbol, orthogonalityProperty, sum_{a mod p} (a/p)=0]
-
A.
orthonormalityRelation
Indicates that a set of vectors are mutually orthogonal and each has unit length with respect to a given inner product.
-
B.
parityProperty
Indicates that a relationship or quantity has a specific parity (such as being even, odd, or matching in parity) according to the defined property.
-
C.
orthographicProperty
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
D.
perpendicularTo
Indicates that one entity is oriented at a right angle (90 degrees) to another entity.
-
E.
diagonalProperty
Indicates a relationship where something possesses or exhibits a diagonal characteristic, alignment, or behavior relative to a reference frame or structure.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ea61248190886e8e55b42ba5f1 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.