Triple

T2417636
Position Surface form Disambiguated ID Type / Status
Subject Zihlkanal E52342 entity
Predicate flowsThrough P225 FINISHED
Object Seeland region E63063 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: Seeland region | Statement: [Zihlkanal, flowsThrough, Seeland region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seeland region
Context triple: [Zihlkanal, flowsThrough, Seeland region]
  • A. Seeland region chosen
    The Seeland region is an area in western Switzerland known for its lakes, fertile plains, and intensive agriculture, particularly vegetable farming.
  • B. Taunus region
    The Taunus region is a low mountain range in Hesse, Germany, known for its forested hills, spa towns, and historical castles overlooking the Rhine-Main area.
  • C. Eurobodalla region
    The Eurobodalla region is a coastal area in southeastern New South Wales, Australia, known for its beaches, national parks, and rural towns centered around Batemans Bay, Moruya, and Narooma.
  • D. Lika region
    The Lika region is a mountainous and sparsely populated area of central Croatia known for its karst landscapes, forests, and traditional rural culture.
  • E. Karas Region
    Karas Region is the southernmost administrative region of Namibia, known for its arid landscapes, desert scenery, and coastal towns along the Atlantic Ocean.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc94eafd481909eeff689e5bf5960 completed March 7, 2026, 6:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf4dcf6c8190a51f26af7e7a9b9c completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:42 p.m.