Triple
T2663236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hrodna |
E54772
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Гродна |
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: Гродна | Statement: [Hrodna, alternativeName, Гродна]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Гродна Context triple: [Hrodna, alternativeName, Гродна]
-
A.
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.
-
B.
Novopolotsk
Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
-
C.
Mogilev
Mogilev is a major city in eastern Belarus known as an important industrial and cultural center on the Dnieper River.
-
D.
Minsk
Minsk is the capital and largest city of Belarus, serving as its political, economic, and cultural center.
-
E.
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.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96b9f1c8190a8a9460ca88a9aaf |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055bd41108190920b7397c16d15f5 |
completed | March 10, 2026, 5:32 p.m. |
Created at: March 6, 2026, 9:53 p.m.