Triple
T8024772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Admiralteysky Prospekt |
E186824
|
entity |
| Predicate | officialLanguageOfToponym |
P24399
|
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: [Admiralteysky Prospekt, officialLanguageOfToponym, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialLanguageOfToponym Context triple: [Admiralteysky Prospekt, officialLanguageOfToponym, Russian]
-
A.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
C.
languageOfHistoricName
Indicates the language in which a historic or former name of an entity is expressed.
-
D.
nationalLanguageStandardizedIn
Indicates that a national language has been formally standardized or codified within a particular country or jurisdiction.
-
E.
historicallyDominantLanguageOfAdministrationIn
Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
- 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_69ca82ad4e2c8190a693e3c9e30fe66f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e90c7348190abc1013a312e4f1a |
completed | March 31, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69cb049253d08190bafcecfde493ab8b |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:21 p.m.