Triple

T16460383
Position Surface form Disambiguated ID Type / Status
Subject Lyss E399789 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Aarberg E305856 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: Aarberg | Statement: [Lyss, hasNeighboringMunicipality, Aarberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aarberg
Context triple: [Lyss, hasNeighboringMunicipality, Aarberg]
  • A. Aarberg chosen
    Aarberg is a small historic town in the canton of Bern in Switzerland, known for its medieval center and distinctive wooden bridge over the Aare River.
  • B. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • C. Aarburg
    Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
  • D. Zugerberg
    Zugerberg is a scenic mountain and recreational area in the Swiss canton of Zug, known for its panoramic views over Lake Zug and the surrounding Alps.
  • E. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d80e66c8190b2b3199efe9cfaa1 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a005817fa088190a0eb85016fe5afc4 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:10 a.m.