Triple

T21375782
Position Surface form Disambiguated ID Type / Status
Subject Třebíč E527197 entity
Predicate hasTwinTown P919 FINISHED
Object Humenné 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: Humenné | Statement: [Třebíč, hasTwinTown, Humenné]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Humenné
Context triple: [Třebíč, 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. Hartmanice
    Hartmanice is a small town in the Plzeň Region of the Czech Republic, known for its location in the Šumava (Bohemian Forest) area.
  • D. Huchnom
    Huchnom refers to a subgroup of the Yuki people, an Indigenous group native to what is now Northern California.
  • E. Hrebienok
    Hrebienok is a popular mountain tourist resort and trailhead in the High Tatras of Slovakia, known for its easy cable car access and hiking routes.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bb031988190ae587730a2131a50 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 5:11 p.m.