Triple
T17811759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tambov Oblast |
E444723
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Tambov (city) |
—
|
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: Tambov (city) | Statement: [Tambov Oblast, namedAfter, Tambov (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tambov (city) Context triple: [Tambov Oblast, namedAfter, Tambov (city)]
-
A.
Tambov
chosen
Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
-
B.
Murom
Murom is an ancient Russian city in Vladimir Oblast, known as one of the oldest settlements in Russia and a historic center of Eastern Orthodox culture.
-
C.
Balakovo
Balakovo is a city in Russia’s Saratov Oblast known as an industrial and energy hub on the Volga River.
-
D.
Воткинск
Воткинск — это промышленный город в Удмуртской Республике России, известный как родина композитора Петра Чайковского и центр машиностроения.
-
E.
Lipetsk
Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887b5e50819098506f0b92d709b5 |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.