Triple

T18613136
Position Surface form Disambiguated ID Type / Status
Subject Canton of Bernese Oberland E454948 entity
Predicate contains P35 FINISHED
Object Niesen 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: Niesen | Statement: [Canton of Bernese Oberland, contains, Niesen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niesen
Context triple: [Canton of Bernese Oberland, contains, Niesen]
  • A. Niesen chosen
    Niesen is a prominent pyramid-shaped mountain in the Swiss Alps overlooking Lake Thun in the Bernese Oberland.
  • B. Nennig
    Nennig is a village in southwestern Germany on the Moselle River, known for its Roman villa remains and its location opposite the Luxembourg town of Remich.
  • C. Nisenan
    The Nisenan are an Indigenous people of Northern California, traditionally inhabiting the Sierra Nevada foothills and Sacramento Valley, with a distinct Maidu language and culture.
  • D. Erkheim
    Erkheim is a small municipality in the Unterallgäu district of Bavaria in southern Germany.
  • E. Wasigny
    Wasigny is a small commune in the Ardennes department of northern France, known for its historic medieval architecture and rural character.
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54d030d488190a992d10d3d28b4ad completed April 19, 2026, 9:45 p.m.
Created at: April 10, 2026, 11:45 a.m.