Triple
T22437968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bessel functions |
E554675
|
entity |
| Predicate | ariseInProblemsWith |
P115995
|
FINISHED |
| Object | cylindrical symmetry |
—
|
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: cylindrical symmetry | Statement: [Bessel functions, ariseInProblemsWith, cylindrical symmetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ariseInProblemsWith Context triple: [Bessel functions, ariseInProblemsWith, cylindrical symmetry]
-
A.
facingIssue
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
-
B.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
C.
typicalProblem
chosen
Indicates that a situation, issue, or obstacle is representative or characteristic of the usual problems encountered in a given context.
-
D.
involvesIssue
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
E.
hadMultipleIssues
Indicates that the subject experienced more than one problem, error, or issue in the relevant context.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15adf52f08190a5b592be3e68af0f |
completed | April 29, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.