Triple

T7875636
Position Surface form Disambiguated ID Type / Status
Subject Prättigau/Davos Region E182843 entity
Predicate hasRiver P165 FINISHED
Object Landwasser E183972 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: Landwasser | Statement: [Prättigau/Davos Region, hasRiver, Landwasser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Landwasser
Context triple: [Prättigau/Davos Region, hasRiver, Landwasser]
  • A. Landwasser chosen
    Landwasser is a river in the canton of Graubünden in eastern Switzerland that flows through the alpine town of Davos.
  • B. O Lago
    O Lago is a modernist painting by Brazilian artist Tarsila do Amaral, reflecting her signature vibrant colors and stylized forms inspired by Brazilian landscapes and culture.
  • C. Achterwasser
    Achterwasser is a coastal lagoon on the German island of Usedom, connected to the Baltic Sea and known for its shallow waters and scenic natural surroundings.
  • D. Wateren
    Wateren is a small village in the Dutch province of Drenthe, known for its rural character and proximity to heathlands and forests.
  • E. Karosta
    Karosta is a historic former military port district in the Latvian city of Liepāja, known for its Tsarist-era fortifications, Soviet naval heritage, and distinctive coastal landscape.
  • 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_69ca828a17248190b46defe758bc5ad3 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39aa7ca88190b88a18f6a8971e51 completed March 31, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b79705c8190955e128081048ebe completed March 31, 2026, 5:28 a.m.
Created at: March 30, 2026, 4:57 p.m.