Triple
T22967249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konotop Uyezd |
E571078
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Konotop |
—
|
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: Konotop | Statement: [Konotop Uyezd, namedAfter, Konotop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konotop Context triple: [Konotop Uyezd, namedAfter, Konotop]
-
A.
Konotop
chosen
Konotop is a historic city in northeastern Ukraine, known for the 1659 Battle of Konotop and its role as a regional railway and industrial center.
-
B.
Horlivka
Horlivka is an industrial city in eastern Ukraine’s Donetsk region, known for its coal mining and chemical industries and its location within the contested Donbas area.
-
C.
Kostiantynivka
Kostiantynivka is an industrial city in eastern Ukraine known for its metallurgical and glass production and its strategic location within Donetsk Oblast.
-
D.
Kremenets
Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
-
E.
Kamenets-Podolsk
Kamenets-Podolsk is a historic city in western Ukraine that became the site of one of the earliest and largest mass shootings of Jews during the Holocaust.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1822f57088190addc6857063b4cca |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:48 p.m.