Triple
T4465635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyiv Metro |
E98369
|
entity |
| Predicate | formerLanguageOfSignage |
P28976
|
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: [Kyiv Metro, formerLanguageOfSignage, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerLanguageOfSignage Context triple: [Kyiv Metro, formerLanguageOfSignage, Russian]
-
A.
officialLanguageOfSignage
Indicates that a particular language is the one officially used on public signs and signage within a given place or context.
-
B.
formerLanguage
chosen
Indicates that one entity was previously the language of another entity but is no longer in that role.
-
C.
tertiaryLanguageOfSignage
Indicates that a language is used as the third-most prominent language on signage in a given context or location.
-
D.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
E.
signatureLanguage
Indicates the language in which a signature (e.g., on a document or agreement) is written or expressed.
- 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356991a588190be2f95fd957d7f99 |
completed | March 13, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69b34f65f6448190abfadb2ae5658798 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:34 p.m.