Triple
T2663746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plzeň Region |
E54782
|
entity |
| Predicate | hasSignificantRiver |
P165
|
FINISHED |
| Object | Radbuza |
E110841
|
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: Radbuza | Statement: [Plzeň Region, hasSignificantRiver, Radbuza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radbuza Context triple: [Plzeň Region, hasSignificantRiver, Radbuza]
-
A.
Radbuza
chosen
Radbuza is a river in the Czech Republic that flows through western Bohemia and is one of the main rivers running through the city of Plzeň.
-
B.
Orzola
Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
-
C.
Kuzminki
Kuzminki is a Moscow Metro station on the Tagansko–Krasnopresnenskaya Line serving the Kuzminki District in southeastern Moscow.
-
D.
Ruda
Ruda is the former name of the global sportswear and athletic brand now known as Puma.
-
E.
Trebsen
Trebsen is a small town in the Free State of Saxony in eastern Germany, known for its historic castle and location along the Mulde 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96b9f1c8190a8a9460ca88a9aaf |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98dc36d8819086fc739c324f0761 |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:54 p.m.