Triple
T1753044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Dnieper |
E38489
|
entity |
| Predicate | keyCity |
P235
|
FINISHED |
| Object | Zaporizhzhia |
E115557
|
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: Zaporizhzhia | Statement: [Battle of the Dnieper, keyCity, Zaporizhzhia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaporizhzhia Context triple: [Battle of the Dnieper, keyCity, Zaporizhzhia]
-
A.
Donetsk
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
-
B.
Zaporizhzhia Oblast
chosen
Zaporizhzhia Oblast is a southeastern region of Ukraine that has become a major frontline area and strategic hotspot during the ongoing conflict with Russia.
-
C.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
D.
Kherson Oblast
Kherson Oblast is a strategically important region in southern Ukraine, known for its Black Sea and Dnipro River access and as a major battleground during the Russo-Ukrainian War.
-
E.
Dnipropetrovsk Oblast
Dnipropetrovsk Oblast is a large industrial and mining region in central-eastern Ukraine, known for its major cities, heavy industry, and significant role in the country’s economy.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa641432d88190ab4254cb4c3ad402 |
completed | March 6, 2026, 5:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae651c82588190b9f1461a7e135670 |
completed | March 9, 2026, 6:13 a.m. |
Created at: March 4, 2026, 7:31 p.m.