Triple

T21483392
Position Surface form Disambiguated ID Type / Status
Subject Filmové studio Barrandov E530054 entity
Predicate locatedIn P40 FINISHED
Object Prague 5 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: Prague 5 | Statement: [Filmové studio Barrandov, locatedIn, Prague 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prague 5
Context triple: [Filmové studio Barrandov, locatedIn, Prague 5]
  • A. Prague 5 chosen
    Prague 5 is a large municipal district of Prague known for its mix of residential neighborhoods, commercial areas, and green spaces on the western side of the city.
  • B. Prague 4
    Prague 4 is a large administrative district in the southern part of Prague, Czech Republic, combining residential neighborhoods, business areas, and significant transport routes.
  • C. Prague 10
    Prague 10 is one of the administrative districts of Prague, Czech Republic, encompassing mainly residential neighborhoods and parts of the city’s eastern area.
  • 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. Prague 8
    Prague 8 is a municipal district of Prague that includes a mix of historic neighborhoods and modern residential and commercial areas along the northeastern part of the city.
  • 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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea35945481909e5982429962de39 completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:21 p.m.