Triple
T4165843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZF |
E84442
|
entity |
| Predicate | consistencyQuestion |
P28011
|
FINISHED |
| Object | relative to large cardinal axioms |
—
|
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: relative to large cardinal axioms | Statement: [ZF, consistencyQuestion, relative to large cardinal axioms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consistencyQuestion Context triple: [ZF, consistencyQuestion, relative to large cardinal axioms]
-
A.
typicalConsistency
Indicates that one entity characteristically maintains a regular or expected level of consistency in relation to another entity or context.
-
B.
isInconsistent
Indicates that there is a logical or factual contradiction within or between the entities or statements involved.
-
C.
consistentWith
Indicates that one entity does not contradict and is compatible or in agreement with another entity, condition, or set of constraints.
-
D.
isEquiconsistentWith
chosen
Indicates that two formal theories or systems have the same consistency strength, such that if one is consistent then the other is also consistent, and if one is inconsistent then so is the other.
-
E.
questionFormulation
Indicates that one entity formulates, poses, or expresses a question directed toward another entity or 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02ac8e788190a8f3563a2903bbad |
completed | March 9, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69af018fb0948190a9701b2e8e5d9bac |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.