Triple
T4797671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Úslava |
E106751
|
entity |
| Predicate | mouthOfWatercourse |
P3817
|
FINISHED |
| Object | Berounka |
E289129
|
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: Berounka | Statement: [Úslava, mouthOfWatercourse, Berounka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berounka Context triple: [Úslava, mouthOfWatercourse, Berounka]
-
A.
Berounka
chosen
Berounka is a major river in western Bohemia in the Czech Republic, known for flowing through the Plzeň Region and eventually joining the Vltava near Prague.
-
B.
Svitava
Svitava is a river in the Czech Republic that flows through the city of Brno and is one of its main waterways.
-
C.
Blšanka
Blšanka is a small river in the Czech Republic that flows through the Ústí nad Labem and Karlovy Vary regions before joining the Ohře River.
-
D.
Lučina
Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
-
E.
Brda
Brda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic landscapes and popular kayaking routes.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6632708c8190b627d99363ab062c |
completed | March 20, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be778861a88190bf7c9f04d903a5e2 |
completed | March 21, 2026, 10:48 a.m. |
Created at: March 20, 2026, 1:22 p.m.