Triple

T7151260
Position Surface form Disambiguated ID Type / Status
Subject Troja E166695 entity
Predicate near P350 FINISHED
Object Holešovice E646477 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: Holešovice | Statement: [Troja, near, Holešovice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holešovice
Context triple: [Troja, near, 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. 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.
  • C. Žižkov
    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.
  • D. Prague 6
    Prague 6 is a large municipal district of Prague, Czech Republic, known for its residential neighborhoods, diplomatic quarter, and proximity to Prague Castle and the airport.
  • E. Tuchkovo
    Tuchkovo is an urban-type settlement in Moscow Oblast, Russia, located west of Moscow and known for its proximity to the Ruza Reservoir and regional transport links.
  • 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_69c68886779c8190a8e3fbabffe68253 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7f3e4a88190a3110f2368262528 completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf817e4c819098268479f3fb181f completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:46 p.m.