Triple
T62995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Rule |
E1249
|
entity |
| Predicate | logicalStructure |
P841
|
FINISHED |
| Object | self-referential moral test |
—
|
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: self-referential moral test | Statement: [Golden Rule, logicalStructure, self-referential moral test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: logicalStructure Context triple: [Golden Rule, logicalStructure, self-referential moral test]
-
A.
hasStructureType
chosen
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
B.
namingStructure
Indicates a relationship where one entity defines, organizes, or constrains the naming or label format used for another entity.
-
C.
hasOrganizationalStructure
Indicates that an entity possesses a defined internal arrangement of roles, responsibilities, and relationships that determine how it is organized and operates.
-
D.
dataModel
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
E.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea3c44081908fa3856969881d1f |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.