Triple

T21830188
Position Surface form Disambiguated ID Type / Status
Subject Svatava Pírková-Jakobson E538972 entity
Predicate givenName P17 FINISHED
Object Svatava NE NERFINISHED

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: Svatava | Statement: [Svatava Pírková-Jakobson, givenName, Svatava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svatava
Context triple: [Svatava Pírková-Jakobson, givenName, Svatava]
  • A. Svatava chosen
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • B. 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.
  • C. Osek
    Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
  • D. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • E. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0913554508190b81347f01d3903e8 completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:54 p.m.