Triple
T20028782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Podol |
E495062
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Moscow region |
—
|
NE NERFINISHED |
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: Moscow region | Statement: [Podol, partOf, Moscow region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moscow region Context triple: [Podol, partOf, Moscow region]
-
A.
Moscow Oblast
chosen
Moscow Oblast is a federal subject of Russia that surrounds, but does not include, the city of Moscow and serves as a major industrial and population center in western Russia.
-
B.
Moscow Governorate
Moscow Governorate was a major administrative division of the Russian Empire centered around Moscow, serving as a key political, economic, and cultural region.
-
C.
Tver Oblast
Tver Oblast is a federal subject of western Russia known for its forests, lakes, and historic towns, and for encompassing the headwaters of major rivers including the Volga.
-
D.
Ryazan Oblast
Ryazan Oblast is a federal subject of central Russia known for its historic cities, agricultural landscapes, and location along the Oka River southeast of Moscow.
-
E.
Belgorod region
The Belgorod region is an area in western Russia near the Ukrainian border, historically notable as a major World War II battleground and now an important agricultural and industrial region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662908df081909a6c8ccf0dd90fff |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.