Triple

T11131834
Position Surface form Disambiguated ID Type / Status
Subject Náchod E263301 entity
Predicate hasNearbyTown P3883 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, hasNearbyTown, Česká Skalice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Česká Skalice
Context triple: [Náchod, hasNearbyTown, 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e831f4808190afabdaa0e97bbe32 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441e6b72881908f8288e99df0cb7c completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:28 p.m.