Triple

T2044999
Position Surface form Disambiguated ID Type / Status
Subject László Löwenstein E45430 entity
Predicate placeOfBirth P1 FINISHED
Object Ružomberok E40882 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: Ružomberok | Statement: [László Löwenstein, placeOfBirth, Ružomberok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ružomberok
Context triple: [László Löwenstein, placeOfBirth, Ružomberok]
  • A. Ružomberok chosen
    Ružomberok is a town in northern Slovakia known for its location in the Liptov region and its historical and cultural significance.
  • B. Prešporok
    Prešporok is the historical Slovak name for the city now known as Bratislava, the capital of Slovakia.
  • C. Bruntál
    Bruntál is a historic town in the Moravian-Silesian Region of the Czech Republic, known as one of the oldest towns in the country and a gateway to the Jeseníky Mountains.
  • D. Sedlčany
    Sedlčany is a small historic town in the Czech Republic known for its traditional cheese production and location on the Mastník River.
  • E. Dubnica nad Váhom
    Dubnica nad Váhom is a town in western Slovakia known as an industrial center and the hometown of several notable Slovak athletes.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9728f688190939d7c4df524f9b4 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae893779648190ae0d039c614736c8 completed March 9, 2026, 8:47 a.m.
Created at: March 4, 2026, 7:39 p.m.