Triple
T2504635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga Korbut |
E52548
|
entity |
| Predicate | trainingLocation |
P40
|
FINISHED |
| Object | Grodno |
E54772
|
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: Grodno | Statement: [Olga Korbut, trainingLocation, Grodno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grodno Context triple: [Olga Korbut, trainingLocation, Grodno]
-
A.
Novopolotsk
Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
-
B.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
C.
Hrodna
chosen
Hrodna is a historic city in western Belarus known for its well-preserved architecture and role as a major cultural and economic center of the region.
-
D.
Vilna
Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
-
E.
Mogilev
Mogilev is a major city in eastern Belarus known as an important industrial and cultural center 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cd2db0819087d21ec49ffd9585 |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af654de164819091cf3d5384d7d72c |
completed | March 10, 2026, 12:26 a.m. |
Created at: March 6, 2026, 9:46 p.m.