Triple

T10939362
Position Surface form Disambiguated ID Type / Status
Subject Sanok E258423 entity
Predicate hasTwinTown P919 FINISHED
Object Humenné E315952 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: Humenné | Statement: [Sanok, hasTwinTown, Humenné]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Humenné
Context triple: [Sanok, hasTwinTown, Humenné]
  • A. Humenné chosen
    Humenné is a town in eastern Slovakia known as a regional industrial hub with a significant chemical and machinery sector.
  • B. Husinec
    Husinec is a small Czech town best known as the birthplace of the religious reformer Jan Hus.
  • C. Haná
    Haná is a historical ethnographic region in central Moravia in the Czech Republic, known for its fertile agricultural land, distinctive folk traditions, and Hanakian dialect.
  • D. Hodonín
    Hodonín is a town in the South Moravian Region of the Czech Republic, notable as the birthplace of the first Czechoslovak president Tomáš Garrigue Masaryk.
  • E. Beránek
    Beránek is a Czech surname and word meaning "little lamb," commonly used as a family name in Czech-speaking regions.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c1389881909341170984211810 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c0e940081908c84ea4cf3b877fc completed April 17, 2026, 1:56 p.m.
Created at: April 8, 2026, 9:23 p.m.