Triple
T10083158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherkasy Oblast |
E213950
|
entity |
| Predicate | hasCityStatus |
P3422
|
FINISHED |
| Object | Shpola |
E841412
|
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: Shpola | Statement: [Cherkasy Oblast, hasCityStatus, Shpola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shpola Context triple: [Cherkasy Oblast, hasCityStatus, Shpola]
-
A.
Shpola
chosen
Shpola is a small town in central Ukraine that serves as an administrative center within Cherkasy Oblast.
-
B.
Kremenets
Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
-
C.
Pavlohrad
Pavlohrad is an industrial city in central-eastern Ukraine known for its coal mining, chemical industry, and role as a regional transport hub.
-
D.
Monastyryshche
Monastyryshche is a small town in central Ukraine that serves as a local administrative and cultural center within Cherkasy Oblast.
-
E.
Krasny Kut
Krasny Kut is a small town in southwestern Russia known as an administrative and agricultural center within the Saratov 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04352d081908f676444cd2d2578 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e583ec2c819086429bd6d323d780 |
completed | April 5, 2026, 10:43 p.m. |
Created at: March 30, 2026, 9 p.m.