Triple
T1679962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Ukraine |
E36315
|
entity |
| Predicate | containsAdministrativeRegion |
P285
|
FINISHED |
| Object | City of Kyiv |
E17733
|
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: City of Kyiv | Statement: [Central Ukraine, containsAdministrativeRegion, City of Kyiv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Kyiv Context triple: [Central Ukraine, containsAdministrativeRegion, City of Kyiv]
-
A.
Kyiv
chosen
Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
-
B.
Kievskaya
Kievskaya is a prominent Moscow Metro station complex known for its ornate, Ukrainian-themed architecture and role as a major transfer hub.
-
C.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
-
D.
Nizhyn
Nizhyn is a historic city in northern Ukraine known for its cultural heritage, educational institutions, and well-preserved architecture.
-
E.
Chernihiv
Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial center.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6260afb881909a50e80c8211fa08 |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeac637748190b67ddd9eedc3698d |
completed | March 8, 2026, 9:31 p.m. |
Created at: March 4, 2026, 7:29 p.m.