Triple

T12794621
Position Surface form Disambiguated ID Type / Status
Subject Aarberg E305856 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Kallnach E1043168 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: Kallnach | Statement: [Aarberg, hasNeighboringMunicipality, Kallnach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kallnach
Context triple: [Aarberg, hasNeighboringMunicipality, Kallnach]
  • A. Kallnach chosen
    Kallnach is a municipality in the canton of Bern in Switzerland, located in the Seeland region.
  • B. Beutelsbach
    Beutelsbach is a small municipality in the rural Passau district of Lower Bavaria in southeastern Germany.
  • C. Waldkirch
    Waldkirch is a small historic town in southwestern Germany’s Black Forest region, known for its scenic surroundings and traditional organ-building industry.
  • D. Neuß
    Neuß is an alternative spelling of Neuss, a historic city on the Rhine in North Rhine-Westphalia, Germany.
  • E. Niederlahnstein
    Niederlahnstein is a former town on the right bank of the Rhine in Rhineland-Palatinate, Germany, now part of the city of Lahnstein.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6ca0288190aba01735b71a01da completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76b96f72881909090691e99bb2425 completed May 3, 2026, 3:36 p.m.
Created at: April 9, 2026, 5:30 p.m.