Triple
T9876197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svitava |
E240078
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Blansko |
E429605
|
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: Blansko | Statement: [Svitava, flowsThrough, Blansko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blansko Context triple: [Svitava, flowsThrough, Blansko]
-
A.
Blansko
chosen
Blansko is a small industrial town in the South Moravian Region of the Czech Republic, known as a gateway to the Moravian Karst cave system.
-
B.
Beloslav
Beloslav is a small industrial town in northeastern Bulgaria known for its glass production and proximity to the city of Varna.
-
C.
Preobrajenska
Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
-
D.
Žužemberk
Žužemberk is a small historic town in southeastern Slovenia, known for its medieval castle and picturesque setting along the Krka River.
-
E.
Bednja
Bednja is a river in northern Croatia that flows through the Zagorje region before joining the Drava River.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3fb58d481908407898912c4b4e9 |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d09790c8190be161d2dbef2e881 |
completed | April 5, 2026, 10:44 a.m. |
Created at: March 30, 2026, 8:37 p.m.