Triple

T20631075
Position Surface form Disambiguated ID Type / Status
Subject Apeldoorn E506954 entity
Predicate hasTwinTown P919 FINISHED
Object Jihlava NE NERFINISHED

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: Jihlava | Statement: [Apeldoorn, hasTwinTown, Jihlava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jihlava
Context triple: [Apeldoorn, hasTwinTown, Jihlava]
  • A. Jihlava chosen
    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.
  • B. 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.
  • C. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • 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. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6ad0b0508819093c62a4ceaf860ce completed April 20, 2026, 10:47 p.m.
Created at: April 16, 2026, 11:42 a.m.