Triple
T694056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zermelo–Fraenkel set theory |
E13857
|
entity |
| Predicate | symbolForPrimitiveRelation |
P13707
|
FINISHED |
| Object | ∈ |
—
|
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: ∈ | Statement: [Zermelo–Fraenkel set theory, symbolForPrimitiveRelation, ∈]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolForPrimitiveRelation Context triple: [Zermelo–Fraenkel set theory, symbolForPrimitiveRelation, ∈]
-
A.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
B.
symbolType
chosen
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
C.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
D.
DSTRelation
Indicates a temporal relationship where one event, state, or timestamp is adjusted or interpreted according to Daylight Saving Time rules.
-
E.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0b1e1d08190bdd42f57be5c2a6b |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d23e0a08190b08be9d1eff2a1bb |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.