Triple
T8937196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minsk Governorate |
E212805
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object | Bobruisk |
E295542
|
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: Bobruisk | Statement: [Minsk Governorate, containsAdministrativeTerritorialEntity, Bobruisk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobruisk Context triple: [Minsk Governorate, containsAdministrativeTerritorialEntity, Bobruisk]
-
A.
Babruysk
chosen
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
-
B.
Vyazma
Vyazma is a historic town in Smolensk Oblast, western Russia, known for its strategic military significance, particularly during World War II.
-
C.
Baranavichy
Baranavichy is a significant industrial and railway hub city in western Belarus.
-
D.
Orsha
Orsha is a historic city in eastern Belarus known as a regional transport hub and site of several significant battles.
-
E.
Vitebsk
Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b3628881909544507628980c25 |
completed | April 1, 2026, 12:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d02fa2958881908575b7b1e9b40a5e |
completed | April 3, 2026, 9:22 p.m. |
Created at: March 30, 2026, 6:58 p.m.