Triple

T16210520
Position Surface form Disambiguated ID Type / Status
Subject Prague 2 E393450 entity
Predicate contains P35 FINISHED
Object Karlovo náměstí E1209012 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: Karlovo náměstí | Statement: [Prague 2, contains, Karlovo náměstí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karlovo náměstí
Context triple: [Prague 2, contains, Karlovo náměstí]
  • A. Karlovo náměstí chosen
    Karlovo náměstí is a major metro station and public square in central Prague, known as an important transport hub and urban landmark.
  • B. 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.
  • C. Hradčanské náměstí
    Hradčanské náměstí is a historic square in Prague situated by Prague Castle, known for its grand palaces, churches, and panoramic city views.
  • D. Husovo náměstí
    Husovo náměstí is the central historic town square of Beroun in the Czech Republic, known for its traditional architecture and local civic life.
  • E. Malostranské náměstí
    Malostranské náměstí is a historic square in Prague’s Lesser Town known for its Baroque architecture, churches, and role as a central hub beneath Prague Castle.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22713282481909c7c0d0782213461 completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00354a20d081908288fb8c0e8b83b6 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 5:03 a.m.