Triple
T738047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | von Neumann universe |
E14977
|
entity |
| Predicate | V_1Contains |
P19434
|
FINISHED |
| Object | all subsets of the empty set |
—
|
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 subsets of the empty set | Statement: [von Neumann universe, V_1Contains, all subsets of the empty set]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: V_1Contains Context triple: [von Neumann universe, V_1Contains, all subsets of the empty set]
-
A.
includesElement
Indicates that one collection, set, or structure contains a specified element as a member or component.
-
B.
containsFast
Indicates that one entity includes or holds another entity in a way that allows rapid or high-speed access, interaction, or processing.
-
C.
containsMostOf
Indicates that one entity includes the majority (but not necessarily all) of the substance, elements, or components of another entity.
-
D.
containsVowelLetters
Indicates that the subject includes one or more vowel letters within its sequence of characters.
-
E.
containsPoint
Indicates that a geometric region or shape includes a given point within its boundaries.
- 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.