Triple
T10798818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Náchod District |
E254783
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Česká Skalice |
E251627
|
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: Česká Skalice | Statement: [Náchod District, contains, Česká Skalice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Česká Skalice Context triple: [Náchod District, contains, Česká Skalice]
-
A.
Česká Skalice
chosen
Česká Skalice is a small historic town in northeastern Bohemia in the Czech Republic, known for its cultural heritage and proximity to the Rozkoš Reservoir.
-
B.
Slaná
Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
-
C.
Kralupy nad Vltavou
Kralupy nad Vltavou is a town in the Czech Republic situated on the Vltava River, known for its chemical industry and role as a regional transport hub.
-
D.
Schlettau
Schlettau is a small locality in the town of Wettin-Löbejün in the German state of Saxony-Anhalt.
-
E.
Slaný
Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73334feb08190aae967eaa37659f7 |
completed | April 9, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de566352608190ab15e3a4b690c9a5 |
completed | April 14, 2026, 2:59 p.m. |
Created at: April 8, 2026, 9:17 p.m.