Triple

T18351813
Position Surface form Disambiguated ID Type / Status
Subject Prague 3 E439683 entity
Predicate contains P35 FINISHED
Object Žižkov 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: Žižkov | Statement: [Prague 3, contains, Žižkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Žižkov
Context triple: [Prague 3, contains, Žižkov]
  • A. Žižkov chosen
    Žižkov is a historic, traditionally working-class district of Prague known for its dense urban fabric, vibrant nightlife, and notable landmarks such as the Žižkov Television Tower and several important cemeteries.
  • B. Vršovice
    Vršovice is a district in Prague, Czech Republic, known for its residential neighborhoods, sports facilities, and historic architecture.
  • C. Hradčany
    Hradčany is the historic castle district of Prague, known for encompassing Prague Castle and many of the city's most important cultural and political landmarks.
  • D. Prague 7
    Prague 7 is a municipal district of Prague, Czech Republic, known for its residential neighborhoods, parks, and cultural institutions along the Vltava River.
  • E. Vinohrady
    Vinohrady is a historic and upscale residential district in Prague known for its elegant Art Nouveau architecture, leafy parks, and vibrant café and nightlife scene.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f8f07c8190a1506d4a327369d0 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.