Triple
T6293559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli numbers |
E141076
|
entity |
| Predicate | parityProperty |
P70733
|
FINISHED |
| Object | B_n = 0 for all odd n > 1 |
—
|
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: B_n = 0 for all odd n > 1 | Statement: [Bernoulli numbers, parityProperty, B_n = 0 for all odd n > 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parityProperty Context triple: [Bernoulli numbers, parityProperty, B_n = 0 for all odd n > 1]
-
A.
parityWith
Indicates that two entities share the same parity, such as both being even or both being odd.
-
B.
parity
Indicates that two quantities share the same evenness or oddness, or more generally that they have equivalent status or value in a given context.
-
C.
evennessProperty
Indicates that a quantity, value, or count has the property of being even, typically divisible into two equal integer parts without remainder.
-
D.
valueParity
Indicates that two compared values share the same parity (both even or both odd), or more generally, how a value’s parity is characterized in a given context.
-
E.
parityMaintainedWith
Indicates that a state of equality or balance (such as value, status, or conditions) is preserved between two entities over time.
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06438654481908c9833c5f0d61773 |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c06284848c8190a0151ff3e8682889 |
completed | March 22, 2026, 9:43 p.m. |
Created at: March 22, 2026, 4:27 p.m.