Triple
T2504636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga Korbut |
E52548
|
entity |
| Predicate | trainingLocation |
P40
|
FINISHED |
| Object | Minsk |
E43503
|
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: Minsk | Statement: [Olga Korbut, trainingLocation, Minsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minsk Context triple: [Olga Korbut, trainingLocation, Minsk]
-
A.
Minsk
chosen
Minsk is the capital and largest city of Belarus, serving as its political, economic, and cultural center.
-
B.
Gomel
Gomel is a major city in southeastern Belarus, serving as an important cultural, industrial, and economic center near the border with Russia and Ukraine.
-
C.
Brest (Belarus)
Brest is a city in southwestern Belarus near the Polish border, known as a major transport hub and for the historic Brest Fortress, a key World War II memorial.
-
D.
Mogilev
Mogilev is a major city in eastern Belarus known as an important industrial and cultural center on the Dnieper River.
-
E.
Vilna
Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
- 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_69af838c9c648190857a6a95dce1c258 |
completed | March 10, 2026, 2:35 a.m. |
Created at: March 6, 2026, 9:46 p.m.