Triple
T8815533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donetsk Oblast |
E209766
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Kramatorsk |
E261065
|
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: Kramatorsk | Statement: [Donetsk Oblast, majorCity, Kramatorsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kramatorsk Context triple: [Donetsk Oblast, majorCity, Kramatorsk]
-
A.
Kramatorsk
chosen
Kramatorsk is an industrial city in eastern Ukraine that has become a key administrative and strategic center in the Donbas region.
-
B.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
C.
Melitopol
Melitopol is a strategically important industrial and transportation hub in southeastern Ukraine, known for its agricultural production and key road and rail connections.
-
D.
Kupiansk
Kupiansk is a strategically important city in Ukraine’s Kharkiv Oblast, serving as a key railway and logistics hub near the front lines of the Russo-Ukrainian War.
-
E.
Dniprodzerzhynsk
Dniprodzerzhynsk (now officially called Kamianske) is an industrial city in central Ukraine known for its heavy industry and metallurgical enterprises along the Dnieper River.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ff2ff248190bafcafe8b3860e53 |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bc96f7288190ab8d1bbf9d428903 |
completed | April 5, 2026, 1:36 a.m. |
Created at: March 30, 2026, 6:45 p.m.