Triple
T4891148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tula Oblast |
E109563
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Shchyokino |
E449606
|
NE 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: Shchyokino | Statement: [Tula Oblast, hasCity, Shchyokino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shchyokino Context triple: [Tula Oblast, hasCity, Shchyokino]
-
A.
Shchyokino
chosen
Shchyokino is a town in Tula Oblast, Russia, known as a local industrial center and the administrative hub of its surrounding district.
-
B.
Tsitska
Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
-
C.
Chernyakhovsky
Chernyakhovsky is a Slavic surname most notably associated with Soviet General Ivan Chernyakhovsky, a prominent commander during World War II.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Zyuzino
Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e07ca10819083f80f12374544b1 |
completed | March 20, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fbf3e74819099910475bbd18734 |
completed | March 21, 2026, 10:15 a.m. |
Created at: March 20, 2026, 1:28 p.m.