Triple

T10074362
Position Surface form Disambiguated ID Type / Status
Subject Five Lakes Region of Bavaria E213711 entity
Predicate hasPart P35 FINISHED
Object Ammersee E41332 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: Ammersee | Statement: [Five Lakes Region of Bavaria, hasPart, Ammersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ammersee
Context triple: [Five Lakes Region of Bavaria, hasPart, Ammersee]
  • A. Ammersee chosen
    Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
  • B. Altmühlsee
    Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
  • C. Starnberger See
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • D. Würmsee
    Würmsee is the historical name of the Bavarian lake now known as Starnberger See, one of Germany’s largest and most famous lakes near Munich.
  • E. Chiemsee
    Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd015ad488190aee3a2bfb58fb855 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3734e5e688190bbfa472547ef65e8 completed April 18, 2026, 12:04 p.m.
Created at: March 30, 2026, 8:59 p.m.