Triple

T18500970
Position Surface form Disambiguated ID Type / Status
Subject Seeland (Bernese Lakeland) E452063 entity
Predicate containsTown P847 FINISHED
Object Nidau 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: Nidau | Statement: [Seeland (Bernese Lakeland), containsTown, Nidau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nidau
Context triple: [Seeland (Bernese Lakeland), containsTown, Nidau]
  • A. Nidau chosen
    Nidau is a small Swiss town in the canton of Bern, situated near Lake Biel and known for its historic old town and role as a local administrative center.
  • B. Nideggen
    Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel region.
  • C. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • D. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • E. Worb
    Worb is a municipality in the canton of Bern in Switzerland, known for its historic village center and proximity to the city of Bern.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e532c43de48190b49b87c1bb591016 completed April 19, 2026, 7:53 p.m.
Created at: April 10, 2026, 11:36 a.m.