Triple

T16972837
Position Surface form Disambiguated ID Type / Status
Subject Svatava E411729 entity
Predicate hasNameInLanguage P15 FINISHED
Object Svatava (Czech) E411729 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: Svatava (Czech) | Statement: [Svatava, hasNameInLanguage, Svatava (Czech)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svatava (Czech)
Context triple: [Svatava, hasNameInLanguage, Svatava (Czech)]
  • 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. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Slavkov u Brna
    Slavkov u Brna is a historic Czech town best known as the site of the Battle of Austerlitz, one of Napoleon’s most famous victories.
  • E. Malostranská
    Malostranská is a Prague Metro station on Line A serving the historic Malá Strana (Lesser Town) district near Prague Castle.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0ae47f08190a13e98d20aba7f16 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d4738fbc819099e8281ebc777091 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.