Triple
T9343697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Habomai Islands |
E224826
|
entity |
| Predicate | languageUsedDeFacto |
P237
|
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: [Habomai Islands, languageUsedDeFacto, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedDeFacto Context triple: [Habomai Islands, languageUsedDeFacto, Russian]
-
A.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
B.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
C.
deFactoLanguage
chosen
Indicates that a language is used in practice as the primary or common language in a context, even if it has no official legal status there.
-
D.
programmingLanguageUsage
Indicates that an entity uses, is implemented in, or otherwise employs a particular programming language.
-
E.
languageUseTrend
Indicates how the use or prevalence of a particular language changes over time within a given population or context.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bb244e88190b269e0bc997f066a |
completed | April 1, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.