Triple
T27891706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governors-General of the Russian Empire |
E705369
|
entity |
| Predicate | usedTitleInRussian |
P73954
|
FINISHED |
| Object | генерал-губернатор |
—
|
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: генерал-губернатор | Statement: [Governors-General of the Russian Empire, usedTitleInRussian, генерал-губернатор]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedTitleInRussian Context triple: [Governors-General of the Russian Empire, usedTitleInRussian, генерал-губернатор]
-
A.
titleInRussian
Indicates that an entity’s title is given or recorded in the Russian language.
-
B.
usedTitleIn
chosen
Indicates that one entity employed or referenced another entity as a title in some context.
-
C.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
D.
usedTitleFrom
Indicates that one entity has employed or adopted the title originating from another entity.
-
E.
usesTitleIn
Indicates that an entity is referred to using a particular title within a specified context or medium.
- 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 6:36 p.m.