Triple

T21462187
Position Surface form Disambiguated ID Type / Status
Subject Karlín E529498 entity
Predicate borderedBy P224 FINISHED
Object Holešovice 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: Holešovice | Statement: [Karlín, borderedBy, Holešovice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holešovice
Context triple: [Karlín, borderedBy, Holešovice]
  • A. 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.
  • B. Vršovice
    Vršovice is a district in Prague, Czech Republic, known for its residential neighborhoods, sports facilities, and historic architecture.
  • C. Prague 7 chosen
    Prague 7 is a municipal district of Prague, Czech Republic, known for its residential neighborhoods, parks, and cultural institutions along the Vltava River.
  • D. 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.
  • E. Hlušovice
    Hlušovice is a small municipality and village in the Olomouc Region of the Czech Republic.
  • 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_69e0c458133481908ae8b41a12c4edec completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9ef0c0881908554977df00604a6 completed April 23, 2026, 9:44 a.m.
Created at: April 16, 2026, 6:09 p.m.