Triple
T15381976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rinat Akhmetov |
E367825
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Donetsk (before 2014) |
E110135
|
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: Donetsk (before 2014) | Statement: [Rinat Akhmetov, residence, Donetsk (before 2014)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donetsk (before 2014) Context triple: [Rinat Akhmetov, residence, Donetsk (before 2014)]
-
A.
Donetsk
chosen
Donetsk is a major industrial city in eastern Ukraine, historically known for its coal mining and steel production.
-
B.
Donetsk Oblast
Donetsk Oblast is an industrial and heavily urbanized region in eastern Ukraine, historically known for coal mining and metallurgy and currently a focal point of the Russo-Ukrainian conflict.
-
C.
Luhansk
Luhansk is a major city in eastern Ukraine, historically an industrial center and currently a focal point in the Russo-Ukrainian conflict.
-
D.
Zaporizhzhia
Zaporizhzhia is a major industrial city in southeastern Ukraine, known for its large hydroelectric power plant on the Dnieper River and its significant role in the country’s energy and manufacturing sectors.
-
E.
Kharkiv
Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff755ffbdc8190825010885e68ebc3 |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 3:19 a.m.