Triple
T36013099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnold diffusion |
E1041764
|
entity |
| Predicate | hasOpenProblemsIn |
P42093
|
FINISHED |
| Object | rigorous estimates of diffusion speed |
—
|
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: rigorous estimates of diffusion speed | Statement: [Arnold diffusion, hasOpenProblemsIn, rigorous estimates of diffusion speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpenProblemsIn Context triple: [Arnold diffusion, hasOpenProblemsIn, rigorous estimates of diffusion speed]
-
A.
hasOpenQuestions
chosen
Indicates that there are unresolved or unanswered issues, problems, or inquiries associated with the referenced entity or context.
-
B.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
-
C.
openProblemAsOf
Indicates that a problem or issue remains unsolved or unresolved as of a specified point in time.
-
D.
hasFirstSolvedProblem
Indicates that an entity is the first one to have successfully solved a particular problem.
-
E.
numberOfProblems
Indicates the quantity or count of problems associated with a given entity or situation.
- 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_69f76e2b981881908e4e160607fa82eb |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: May 3, 2026, 4:07 p.m.