Triple

T20016313
Position Surface form Disambiguated ID Type / Status
Subject Southern Bavaria E494726 entity
Predicate hasLake P1025 FINISHED
Object Ammersee NE NERFINISHED

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: [Southern Bavaria, hasLake, Ammersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ammersee
Context triple: [Southern Bavaria, hasLake, 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. Schliersee
    Schliersee is a picturesque lake and town in the Bavarian Alps of southern Germany, known for its scenic mountain setting and outdoor recreation.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6623cb8188190b95913ffed895930 completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:34 p.m.