Triple
T32214282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skolemization |
E822885
|
entity |
| Predicate | effectOnQuantifiers |
P185231
|
FINISHED |
| Object | removes existential quantifiers |
—
|
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: removes existential quantifiers | Statement: [Skolemization, effectOnQuantifiers, removes existential quantifiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnQuantifiers Context triple: [Skolemization, effectOnQuantifiers, removes existential quantifiers]
-
A.
effectOnUnion
Indicates the impact or influence that something has on a union as a whole.
-
B.
conditionalEffect
Indicates that one event, state, or action occurs or holds only if a specified condition is met.
-
C.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
D.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
E.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 1, 2026, 12:37 a.m.