Triple
T694055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zermelo–Fraenkel set theory |
E13857
|
entity |
| Predicate | hasPrimitiveRelation |
P17549
|
FINISHED |
| Object | membership relation |
—
|
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: membership relation | Statement: [Zermelo–Fraenkel set theory, hasPrimitiveRelation, membership relation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimitiveRelation Context triple: [Zermelo–Fraenkel set theory, hasPrimitiveRelation, membership relation]
-
A.
isPrincipalAssociationOf
Indicates that one entity serves as the primary or main associated counterpart of another entity within a given context or relationship.
-
B.
hasSubcategoryRelation
Indicates that one category is a more specific subdivision or subset of another broader category.
-
C.
supportsRelation
Indicates that one entity provides assistance, endorsement, or structural backing to another entity or its activity.
-
D.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
E.
hasPrimarySee
Indicates that one entity is designated as the main or preferred "see" reference or cross-reference for another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69a49df19c9481909cc9bc33ed7f011b |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.