Triple
T4492915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | constructible universe |
E100621
|
entity |
| Predicate | satisfiesTheory |
P4233
|
FINISHED |
| Object | ZF |
—
|
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: ZF | Statement: [constructible universe, satisfiesTheory, ZF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: satisfiesTheory Context triple: [constructible universe, satisfiesTheory, ZF]
-
A.
satisfies
chosen
Indicates that one entity meets, fulfills, or complies with the requirements, conditions, or expectations specified by another.
-
B.
supportsTheory
Indicates that one entity provides evidence, justification, or endorsement for the validity or acceptance of another entity’s theory.
-
C.
appliesTheory
Indicates that an entity uses or implements a particular theory in analyzing, explaining, or addressing something.
-
D.
hasTheorem
Indicates that one entity (typically a mathematical theory, field, or work) includes, establishes, or is associated with a particular theorem.
-
E.
isSolutionOf
Indicates that one entity is a correct answer or satisfies the conditions of a given problem, equation, or task.
- 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_69bd43cdf15081909a4fa2585ff63b3e |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5570ba0881908f5fb4f8d0730e64 |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:59 p.m.