Triple
T10491054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Союз нерушимый республик свободных |
E247417
|
entity |
| Predicate | семантика |
P83565
|
FINISHED |
| Object | подчёркивает прочность союза республик |
—
|
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: подчёркивает прочность союза республик | Statement: [Союз нерушимый республик свободных, семантика, подчёркивает прочность союза республик]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: семантика Context triple: [Союз нерушимый республик свободных, семантика, подчёркивает прочность союза республик]
-
A.
семантическоеПоле
Indicates that entities are related by belonging to the same semantic field, i.e., they share a common area of meaning or conceptual domain.
-
B.
semanticsDetail
chosen
Indicates a more specific or fine-grained semantic characterization or nuance of a broader meaning or interpretation.
-
C.
semanticRootMeaning
Indicates the fundamental or core meaning that underlies a word, phrase, or expression in a semantic structure.
-
D.
semanticType
Indicates that something belongs to or is categorized under a particular semantic class or type based on its meaning.
-
E.
linguisticSignificance
Indicates the degree to which something is important, influential, or meaningful within a particular language or linguistic system.
- 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, 12:23 p.m.