Triple
T6293568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli numbers |
E141076
|
entity |
| Predicate | generatingFunction |
P46242
|
FINISHED |
| Object | t/(e^t - 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: t/(e^t - 1) | Statement: [Bernoulli numbers, generatingFunction, t/(e^t - 1)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generatingFunction Context triple: [Bernoulli numbers, generatingFunction, t/(e^t - 1)]
-
A.
hasGeneratingFunction
chosen
Indicates that one entity serves as the generating function associated with, or defining, another entity.
-
B.
generators
Indicates that one entity produces, creates, or brings about another entity or outcome, typically as its source or origin.
-
C.
generationMethod
Indicates the process, technique, or procedure by which something is created, produced, or derived.
-
D.
geometricFunction
Indicates a relationship where one entity serves as a geometric transformation or operation that, when applied, produces or modifies another geometric entity.
-
E.
generalizedForm
Indicates that one entity is a more abstract, generalized version or broader form of another entity.
- 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_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. |
Created at: March 22, 2026, 4:27 p.m.