Triple

T17136560
Position Surface form Disambiguated ID Type / Status
Subject Koňský trh E415852 entity
Predicate followedBy P78 FINISHED
Object Václavské náměstí E1215701 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: Václavské náměstí | Statement: [Koňský trh, followedBy, Václavské náměstí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Václavské náměstí
Context triple: [Koňský trh, followedBy, Václavské náměstí]
  • A. Václavské náměstí chosen
    Václavské náměstí is a major historic square and commercial center in Prague, renowned as a traditional site of national gatherings, demonstrations, and key moments in Czech history.
  • B. Karlovo náměstí
    Karlovo náměstí is a major metro station and public square in central Prague, known as an important transport hub and urban landmark.
  • C. 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.
  • D. Hradčanské náměstí
    Hradčanské náměstí is a historic square in Prague situated by Prague Castle, known for its grand palaces, churches, and panoramic city views.
  • E. 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.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2cf1c588190986167adcf4851b5 completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0170e362048190beb72cd6aab496fb completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:36 a.m.