Triple
T9972376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keyboard Monument |
E196237
|
entity |
| Predicate | languageOfKeyboard |
P4149
|
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: [Keyboard Monument, languageOfKeyboard, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfKeyboard Context triple: [Keyboard Monument, languageOfKeyboard, Russian]
-
A.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
B.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
C.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
-
D.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
E.
languageOfInterface
chosen
Indicates the language used by or presented in a user interface.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7bb03688190a3f4fc1988b8fafa |
completed | April 2, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:48 p.m.