Triple

T5685566
Position Surface form Disambiguated ID Type / Status
Subject University of West Bohemia E125305 entity
Predicate locatedIn P40 FINISHED
Object Plzeň E19529 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: Plzeň | Statement: [University of West Bohemia, locatedIn, Plzeň]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plzeň
Context triple: [University of West Bohemia, locatedIn, Plzeň]
  • A. Plzeň chosen
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • B. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • C. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • D. Žatec
    Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
  • E. Jihlava
    Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023ba52b48190b94f8a3ecff61eb4 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c124e449d481909a6aa8e1c6494322 completed March 23, 2026, 11:32 a.m.
Created at: March 22, 2026, 3:44 p.m.