Triple
T16282583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brześć nad Bugiem |
E395303
|
entity |
| Predicate | languageVariantName |
P20733
|
FINISHED |
| Object | Брест |
E41676
|
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: Брест | Statement: [Brześć nad Bugiem, languageVariantName, Брест]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Брест Context triple: [Brześć nad Bugiem, languageVariantName, Брест]
-
A.
Brest (Belarus)
chosen
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.
-
B.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
-
C.
Novopolotsk
Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
-
D.
Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
-
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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24911f11881909c98ddf829f077e9 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c48c5cc8190ba99154e99942316 |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:05 a.m.