Triple

T4797940
Position Surface form Disambiguated ID Type / Status
Subject P E106757 entity
Predicate region 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: [P, region, Plzeň]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plzeň
Context triple: [P, region, 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 river in the Czech Republic that flows through the historical region of Moravia, including the city of Jihlava, before joining the Svratka River.
  • 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_69bd43f591c881909e5a532388b0f3f3 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6632708c8190b627d99363ab062c completed March 20, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfb1324c2c8190ba2a1c5708ba88e5 completed March 22, 2026, 9:06 a.m.
Created at: March 20, 2026, 1:22 p.m.