Triple

T4797665
Position Surface form Disambiguated ID Type / Status
Subject Úhlava E106750 entity
Predicate hasHumanSettlementOnBanks P16159 FINISHED
Object Švihov E471492 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: Švihov | Statement: [Úhlava, hasHumanSettlementOnBanks, Švihov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Švihov
Context triple: [Úhlava, hasHumanSettlementOnBanks, Švihov]
  • A. Švihov chosen
    Švihov is a small town in the Plzeň Region of the Czech Republic, known for its well-preserved water castle and its location on the Úhlava River.
  • B. Osek
    Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
  • C. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • D. Svitavy
    Svitavy is a town in the Czech Republic best known as the birthplace of Oskar Schindler, the industrialist who saved hundreds of Jews during the Holocaust.
  • E. Šamorín
    Šamorín is a small town in southwestern Slovakia known for its equestrian sports complex, proximity to the Danube River, and growing role as a suburban area near Bratislava.
  • 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_69be6f9ee7e481909e1ff78764d0b67d completed March 21, 2026, 10:14 a.m.
Created at: March 20, 2026, 1:22 p.m.