Triple

T17216028
Position Surface form Disambiguated ID Type / Status
Subject M1 motorway (Hungary) E417853 entity
Predicate passesNear P416 FINISHED
Object Tatabánya 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: Tatabánya | Statement: [M1 motorway (Hungary), passesNear, Tatabánya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tatabánya
Context triple: [M1 motorway (Hungary), passesNear, Tatabánya]
  • A. Tatabánya chosen
    Tatabánya is an industrial city in northwestern Hungary known for its mining heritage and role as a regional economic center.
  • B. Budakeszi
    Budakeszi is a small town in Hungary, located just west of Budapest and known for its surrounding forests and natural recreational areas.
  • C. Bátonyterenye
    Bátonyterenye is a small industrial town in northern Hungary known for its mining heritage and location in Nógrád County.
  • D. Törökbálint
    Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
  • E. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc9f96881909eb86786a76e17e4 completed April 19, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:38 a.m.