Triple

T20082133
Position Surface form Disambiguated ID Type / Status
Subject Trmal Villa E500027 entity
Predicate locatedIn P40 FINISHED
Object Prague 10 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 10 | Statement: [Trmal Villa, locatedIn, Prague 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prague 10
Context triple: [Trmal Villa, locatedIn, Prague 10]
  • A. Prague 10 chosen
    Prague 10 is one of the administrative districts of Prague, Czech Republic, encompassing mainly residential neighborhoods and parts of the city’s eastern area.
  • B. Prague 5
    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.
  • C. Prague 9
    Prague 9 is a municipal district of Prague in the Czech Republic, known for its mix of residential areas, industrial zones, and major venues such as large sports and entertainment arenas.
  • D. 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.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e665588a9c8190886b693b13a215a8 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.