Triple

T1839155
Position Surface form Disambiguated ID Type / Status
Subject Chiemsee E41133 entity
Predicate hasIsland P970 FINISHED
Object Frauenchiemsee E41133 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: Frauenchiemsee | Statement: [Chiemsee, hasIsland, Frauenchiemsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frauenchiemsee
Context triple: [Chiemsee, hasIsland, Frauenchiemsee]
  • A. Ammersee
    Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
  • B. Chiemsee chosen
    Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
  • C. Eibsee
    Eibsee is a picturesque alpine lake in Bavaria, Germany, renowned for its clear turquoise waters and dramatic setting at the foot of the Zugspitze.
  • D. Jungfernsee
    Jungfernsee is a scenic lake on the outskirts of Potsdam and Berlin, known for its historic villas, palaces, and location along the former inner German border.
  • E. 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.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03b3eb08190ae68d8476fc89c7f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c482908190b940497fc5d5db60 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:33 p.m.