Triple

T17358613
Position Surface form Disambiguated ID Type / Status
Subject PSP ČR E422008 entity
Predicate buildingLocatedIn P40 FINISHED
Object Malá Strana NE ONNED1

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: Malá Strana | Statement: [PSP ČR, buildingLocatedIn, Malá Strana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malá Strana
Context triple: [PSP ČR, buildingLocatedIn, Malá Strana]
  • A. Malá Strana chosen
    Malá Strana is a historic district of Prague known for its baroque architecture, narrow streets, and location beneath Prague Castle along the Vltava River.
  • B. Hradčany
    Hradčany is the historic castle district of Prague, known for encompassing Prague Castle and many of the city's most important cultural and political landmarks.
  • C. Staroměstská
    Staroměstská is a Prague Metro station on Line A located near the historic Old Town district and major landmarks such as the Old Town Square and Charles Bridge.
  • D. Žižkov
    Žižkov is a historic, traditionally working-class district of Prague known for its dense urban fabric, vibrant nightlife, and notable landmarks such as the Žižkov Television Tower and several important cemeteries.
  • E. Vršovice
    Vršovice is a district in Prague, Czech Republic, known for its residential neighborhoods, sports facilities, and historic architecture.
  • 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a4a37788190b330b7207aa424b6 completed April 19, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01955e4cb481909e3193439bb85cd8 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:44 a.m.