Triple
T10491067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Союз нерушимый республик свободных |
E247417
|
entity |
| Predicate | связанСПонятием |
P37
|
FINISHED |
| Object | дружба народов |
—
|
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: дружба народов | Statement: [Союз нерушимый республик свободных, связанСПонятием, дружба народов]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: связанСПонятием Context triple: [Союз нерушимый республик свободных, связанСПонятием, дружба народов]
-
A.
definitionOfRelatedConcept
Indicates that one concept provides the formal meaning, explanation, or characterization of another closely related concept.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
-
D.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
E.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097d61e08190952d4354ef1bce52 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:24 p.m.