Triple

T21557101
Position Surface form Disambiguated ID Type / Status
Subject Vilvoorde E531920 entity
Predicate hasTwinTown P919 FINISHED
Object Komló 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: Komló | Statement: [Vilvoorde, hasTwinTown, Komló]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komló
Context triple: [Vilvoorde, hasTwinTown, Komló]
  • A. Komló chosen
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • B. 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.
  • C. Mátészalka
    Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
  • D. Százhalombatta
    Százhalombatta is a Hungarian town on the Danube known for its major oil refinery and significant archaeological heritage, including Bronze Age burial mounds.
  • E. Kazincbarcika
    Kazincbarcika is an industrial town in northeastern Hungary, located in Borsod-Abaúj-Zemplén County.
  • 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eed2e04b048190ac3a9913094b4625 completed April 27, 2026, 3:07 a.m.
Created at: April 16, 2026, 6:29 p.m.