Triple

T17142838
Position Surface form Disambiguated ID Type / Status
Subject Baar, Switzerland E416012 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Neuheim E686799 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: Neuheim | Statement: [Baar, Switzerland, hasNeighboringMunicipality, Neuheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neuheim
Context triple: [Baar, Switzerland, hasNeighboringMunicipality, Neuheim]
  • A. Neuheim chosen
    Neuheim is a small Swiss municipality in the canton of Zug, known for its rural character and proximity to larger economic centers.
  • B. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city center.
  • C. Neuenstein
    Neuenstein is a small town in the Hohenlohe region of Baden-Württemberg, Germany, known for its historic castle and role as an administrative center.
  • D. Nettersheim
    Nettersheim is a municipality in the Eifel region of North Rhine-Westphalia, Germany, known for its natural landscapes and archaeological sites.
  • E. Schweinheim
    Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d73c3c81908b875023bb925edb completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0242dc82dc8190a070a4d8532120fc completed May 11, 2026, 8:58 p.m.
Created at: April 10, 2026, 5:36 a.m.