Triple
T738049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | von Neumann universe |
E14977
|
entity |
| Predicate | rankFunctionDomain |
P19435
|
FINISHED |
| Object | all sets |
—
|
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: all sets | Statement: [von Neumann universe, rankFunctionDomain, all sets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankFunctionDomain Context triple: [von Neumann universe, rankFunctionDomain, all sets]
-
A.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
B.
rankingType
Indicates the specific basis or method by which items are ordered or ranked relative to one another.
-
C.
rankFlagFor
Indicates that something is assigned or associated with a specific ranking flag used to mark its status or priority.
-
D.
rankSignificance
Indicates how important or influential one entity is relative to others within a specified context or ordering.
-
E.
rankRange
Indicates that an entity’s rank falls within a specified minimum and maximum range.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a64957ec81909fe2e2dbffd80ed3 |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.