Triple

T12917295
Position Surface form Disambiguated ID Type / Status
Subject Bad Tölz-Wolfratshausen E309018 entity
Predicate hasPart P35 FINISHED
Object Königsdorf E822787 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: Königsdorf | Statement: [Bad Tölz-Wolfratshausen, hasPart, Königsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Königsdorf
Context triple: [Bad Tölz-Wolfratshausen, hasPart, Königsdorf]
  • A. Königsdorf chosen
    Königsdorf is a rural Bavarian municipality in southern Germany, situated in the alpine foothills south of Munich.
  • B. Premnitz
    Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
  • C. Wietzendorf
    Wietzendorf is a small municipality in Lower Saxony, Germany, known for its rural character and location in the Lüneburg Heath region.
  • D. Perasdorf
    Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971a1e8088190af697629baecf59f completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed314bb9481908144c5399aa62ffa completed May 9, 2026, 6:24 a.m.
Created at: April 9, 2026, 5:41 p.m.