Triple

T7913231
Position Surface form Disambiguated ID Type / Status
Subject Günsberg E183750 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Hubersdorf E185445 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: Hubersdorf | Statement: [Günsberg, neighboringMunicipality, Hubersdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hubersdorf
Context triple: [Günsberg, neighboringMunicipality, Hubersdorf]
  • A. Hubersdorf chosen
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • B. Heinersdorf
    Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
  • C. Ebersdorf
    Ebersdorf is a historic town in present-day Germany that once served as the capital of one of the small Reuss principalities.
  • D. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • E. Bohnsdorf
    Bohnsdorf is a residential locality in the southeastern part of Berlin, Germany, known for its suburban character and proximity to the city’s green and lake-rich areas.
  • 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a748f4c8190bcd868de2fcf0b3a completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc936b4d088190bfcfd3bc6c05f7e8 completed April 1, 2026, 3:39 a.m.
Created at: March 30, 2026, 5:04 p.m.