Triple
T8949250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elets Uyezd |
E213301
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Yelets |
E768302
|
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: Yelets | Statement: [Elets Uyezd, namedAfter, Yelets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yelets Context triple: [Elets Uyezd, namedAfter, Yelets]
-
A.
Yelets
chosen
Yelets is a historic city in western Russia known for its medieval origins, traditional lace-making, and role as a regional cultural and economic center.
-
B.
Pervouralsk
Pervouralsk is an industrial city in Russia’s Ural region, known for its metallurgical plants and location near the geographic border between Europe and Asia.
-
C.
Uglich
Uglich is a historic Russian town on the Volga River, known for its medieval architecture and its association with the mysterious death of Tsarevich Dmitry in 1591.
-
D.
Odintsovo
Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
-
E.
Kireyevsk
Kireyevsk is a small industrial town in western Russia known for its coal-mining history and location within the Tula region.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670b5f50819080f1c73992fe5281 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc93c678c81909d2ab68308d7c2f0 |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 6:59 p.m.