Triple
T7420209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | quadratic reciprocity law |
E171226
|
entity |
| Predicate | numberOfProofsByGauss |
P63676
|
FINISHED |
| Object | at least 8 |
—
|
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: at least 8 | Statement: [quadratic reciprocity law, numberOfProofsByGauss, at least 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfProofsByGauss Context triple: [quadratic reciprocity law, numberOfProofsByGauss, at least 8]
-
A.
wasFirstProvedBy
Indicates that a particular statement, theorem, or result was originally and for the first time demonstrated or established as true by a specified agent.
-
B.
hasProofCount
chosen
Indicates the number of proofs or supporting evidential items associated with a given entity or claim.
-
C.
numberOfMillenniumProblems
Indicates the total count of Millennium Problems associated with a given subject or context.
-
D.
statusOfFermatProof
Indicates the current state or condition of the proof related to Fermat’s Last Theorem (e.g., whether it is proposed, verified, refuted, or incomplete).
-
E.
hasTheorem
Indicates that one entity (typically a mathematical theory, field, or work) includes, establishes, or is associated with a particular theorem.
- 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_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. |
Created at: March 27, 2026, 3:11 p.m.