Triple
T24884178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Клязьма |
E622801
|
entity |
| Predicate | регион мира |
P40571
|
FINISHED |
| Object | Центральная часть европейской России |
—
|
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: Центральная часть европейской России | Statement: [Клязьма, регион мира, Центральная часть европейской России]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: регион мира Context triple: [Клязьма, регион мира, Центральная часть европейской России]
-
A.
worldRegion
chosen
Indicates that one entity is a geographic region that encompasses, contains, or is associated with the other entity within the world.
-
B.
geopoliticalRegion
Indicates a relationship where an entity is a defined political or administrative geographic area, such as a country, state, province, or similar region.
-
C.
continentScope
Indicates that something applies within, is limited to, or is defined at the level of a specific continent.
-
D.
continentType
Indicates that one entity is classified as a specific type or category of continent in relation to another entity.
-
E.
continent
Indicates that one entity is a continent on which the other entity is geographically located or to which it belongs.
- 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_69e2fac4aa848190b3446a3922cec150 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:25 a.m.