Triple
T8532328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nizhyn |
E201982
|
entity |
| Predicate | languageWidelyUsed |
P58450
|
FINISHED |
| Object | Russian |
—
|
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: Russian | Statement: [Nizhyn, languageWidelyUsed, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageWidelyUsed Context triple: [Nizhyn, languageWidelyUsed, Russian]
-
A.
languagesUsed
chosen
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
B.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
C.
languageOfProgramming
Indicates that one entity is a programming language used to implement, develop, or script the other entity.
-
D.
programmingLanguageUsage
Indicates that an entity uses, is implemented in, or otherwise employs a particular programming language.
-
E.
usedByProgrammingLanguages
Indicates that something (such as a tool, library, paradigm, or feature) is employed or utilized by one or more programming languages.
- 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe676e2ac8190b65a3d2a935776fd |
completed | March 31, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69cbd111bf988190be98c92a607c6456 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:17 p.m.