Triple

T17992695
Position Surface form Disambiguated ID Type / Status
Subject Gaiziņkalns ski area E430415 entity
Predicate locatedInRegion P40 FINISHED
Object Vidzeme 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: Vidzeme | Statement: [Gaiziņkalns ski area, locatedInRegion, Vidzeme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vidzeme
Context triple: [Gaiziņkalns ski area, locatedInRegion, Vidzeme]
  • A. Vidzeme chosen
    Vidzeme is a historical region in northern Latvia known for its rich cultural heritage, forests, and role in the development of Latvian national identity.
  • B. Kurzeme
    Kurzeme is a historical and cultural region in western Latvia, known for its Baltic Sea coastline, forests, and traditional Latvian heritage.
  • C. Vendryně
    Vendryně is a village in the Moravian-Silesian Region of the Czech Republic, known for its location in the historical region of Cieszyn Silesia near the Olza River.
  • D. Ziem
    Ziem is the surname of French painter Félix Ziem, known for his 19th-century landscapes and Venetian scenes.
  • E. Zwedru
    Zwedru is a major town in eastern Liberia known as an administrative and commercial center for the surrounding region.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2a0f8588190b6090c7cce60a35f completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.