Triple

T22141544
Position Surface form Disambiguated ID Type / Status
Subject Vallader E547169 entity
Predicate hasRegulator P4784 FINISHED
Object Lia Rumantscha 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: Lia Rumantscha | Statement: [Vallader, hasRegulator, Lia Rumantscha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lia Rumantscha
Context triple: [Vallader, hasRegulator, Lia Rumantscha]
  • A. Lia Rumantscha chosen
    Lia Rumantscha is the main organization dedicated to promoting, standardizing, and preserving the Romansh language in Switzerland.
  • B. Grisons
    Grisons is the largest and easternmost canton of Switzerland, known for its mountainous Alpine landscapes and multilingual culture (German, Romansh, and Italian).
  • C. Savognin
    Savognin is a Swiss mountain village and ski resort in the canton of Graubünden, known for its alpine scenery and outdoor recreation.
  • D. Klettgau
    Klettgau is a municipality in the Waldshut district of Baden-Württemberg in southwestern Germany, near the Swiss border, known for its rural character and viticulture.
  • E. Bernese Jura region
    The Bernese Jura region is the French-speaking, predominantly rural and industrial area of the Canton of Bern in Switzerland, known for its Jura mountains landscape and watchmaking tradition.
  • 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129beb6c8819083be3b7479bc032f completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.