Triple
T10060947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Dynamo Brest |
E212985
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Brest, Belarus |
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: Brest, Belarus | Statement: [FC Dynamo Brest, location, Brest, Belarus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brest, Belarus Context triple: [FC Dynamo Brest, location, Brest, Belarus]
-
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.
Brest
Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
-
C.
Minsk
Minsk is the capital and largest city of Belarus, serving as its political, economic, and cultural center.
-
D.
Pinsk
Pinsk is a historic city in southwestern Belarus, known for its location on the Pina River and its rich cultural and architectural heritage.
-
E.
Babruysk
Babruysk is a historic city in eastern Belarus known as a former major Jewish cultural center and regional industrial hub.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcfd1fc98819082ec3f2f91151955 |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b624191c819093b8392b5573fa96 |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 8:57 p.m.