Triple
T1489720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss’s lemma (number theory) |
E29548
|
entity |
| Predicate | equates |
P6530
|
FINISHED |
| Object | Legendre symbol (a|p) with (−1)^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: Legendre symbol (a|p) with (−1)^n | Statement: [Gauss’s lemma (number theory), equates, Legendre symbol (a|p) with (−1)^n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equates Context triple: [Gauss’s lemma (number theory), equates, Legendre symbol (a|p) with (−1)^n]
-
A.
equivalentTo
chosen
Indicates that two entities represent the same concept, value, or state, and can be treated as interchangeable in the given context.
-
B.
quantifies
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
-
C.
expresses
Indicates that one entity conveys, communicates, or articulates a thought, feeling, or idea through another medium or form.
-
D.
ensures
Indicates that one entity guarantees or makes certain that a particular condition, outcome, or state holds for another entity or situation.
-
E.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c233ec819087e1233af02aabfc |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.