Triple

T10092760
Position Surface form Disambiguated ID Type / Status
Subject Northern Hungary E215782 entity
Predicate containsSpaTown P19664 FINISHED
Object Miskolctapolca E38152 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: Miskolctapolca | Statement: [Northern Hungary, containsSpaTown, Miskolctapolca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miskolctapolca
Context triple: [Northern Hungary, containsSpaTown, Miskolctapolca]
  • A. Miskolc chosen
    Miskolc is a large industrial and cultural city in northeastern Hungary, known for its steel industry, historic center, and nearby cave baths.
  • B. Törökszentmiklós
    Törökszentmiklós is a town in central-eastern Hungary known for its agricultural surroundings and location within the Great Hungarian Plain.
  • C. Mátészalka
    Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
  • D. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • E. Rákosszentmihály
    Rákosszentmihály is a residential neighborhood in the 16th district of Budapest, known for its suburban character and family-friendly environment.
  • 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_69ca83a4947c8190823a7495dc5d96ed completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd05c3c0c8190927580717429a4e5 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d354e57ea88190922e7eee07fd86f2 completed April 6, 2026, 6:38 a.m.
Created at: March 30, 2026, 9:01 p.m.