Triple

T19827636
Position Surface form Disambiguated ID Type / Status
Subject Novi Bečej E476368 entity
Predicate hasAlternativeName P39 FINISHED
Object Újbecse 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: Újbecse | Statement: [Novi Bečej, hasAlternativeName, Újbecse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Újbecse
Context triple: [Novi Bečej, hasAlternativeName, Újbecse]
  • A. Törökbecse chosen
    Törökbecse is the Hungarian name for Novi Bečej, a town in the Vojvodina region of northern Serbia.
  • B. Bicske
    Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
  • C. Besztercebánya
    Besztercebánya is a historic mining and cultural city in central Slovakia, known in Hungarian as Besztercebánya and in Slovak as Banská Bystrica.
  • D. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • E. Bácska
    Bácska is a historical region in the Pannonian Plain, today divided between northern Serbia and southern Hungary, known for its multicultural population and agricultural importance.
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656cc0f2c81908137caa4c2087027 completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.