Triple
T2098150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Ukraine |
E37029
|
entity |
| Predicate | hasMajorCity |
P316
|
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: [Southern Ukraine, hasMajorCity, Zaporizhzhia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaporizhzhia Context triple: [Southern Ukraine, hasMajorCity, 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.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
D.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
E.
Kherson
Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9de75c81909770409b5ae62c24 |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6251b848190911748bd72b3dc25 |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 4, 2026, 7:43 p.m.