Triple

T19617489
Position Surface form Disambiguated ID Type / Status
Subject Republic Square, Plzeň E470905 entity
Predicate hasNameInCzech P17790 FINISHED
Object Náměstí Republiky 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: Náměstí Republiky | Statement: [Republic Square, Plzeň, hasNameInCzech, Náměstí Republiky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Náměstí Republiky
Context triple: [Republic Square, Plzeň, hasNameInCzech, Náměstí Republiky]
  • A. Náměstí Republiky chosen
    Náměstí Republiky is a central square in Prague known for its historic buildings, major shopping venues, and role as a key urban and transport hub.
  • B. Masaryk Square
    Masaryk Square is the central historic town square and main public gathering place in the Czech town of Uherské Hradiště.
  • C. Karlovo náměstí
    Karlovo náměstí is a major metro station and public square in central Prague, known as an important transport hub and urban landmark.
  • D. Karlínské náměstí
    Karlínské náměstí is a central square in Prague’s Karlín district, known for its historic architecture, park space, and the Church of Saints Cyril and Methodius.
  • E. Hradčanské náměstí
    Hradčanské náměstí is a historic square in Prague situated by Prague Castle, known for its grand palaces, churches, and panoramic city views.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e346548190b12e38d716bdfc4f completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:43 p.m.