Triple
T20049557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merefa |
E499155
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Kharkiv metropolitan area |
—
|
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: Kharkiv metropolitan area | Statement: [Merefa, partOf, Kharkiv metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kharkiv metropolitan area Context triple: [Merefa, partOf, Kharkiv metropolitan area]
-
A.
Kharkiv
chosen
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
B.
Oleksandriia
Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
-
C.
Kirovograd
Kirovograd is a city in central Ukraine, historically significant as a strategic site during World War II and now known as Kropyvnytskyi.
-
D.
Kremenchuk
Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
-
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 (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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:37 p.m.