Triple

T11352679
Position Surface form Disambiguated ID Type / Status
Subject Banská Bystrica Region E268872 entity
Predicate containsRiver P165 FINISHED
Object Slaná E847787 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: Slaná | Statement: [Banská Bystrica Region, containsRiver, Slaná]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slaná
Context triple: [Banská Bystrica Region, containsRiver, Slaná]
  • A. Slaná chosen
    Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
  • B. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • C. Vodňany
    Vodňany is a small historic town in the South Bohemian Region of the Czech Republic, known for its traditional fishpond farming and picturesque rural character.
  • D. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • E. Moravice
    Moravice is a river in the northern part of the historical Moravia region of the Czech Republic.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea24489081908fbf47fd2e6d709c completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e62442905881909c5228a58d9dea3d completed April 20, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:33 p.m.