Triple

T13821335
Position Surface form Disambiguated ID Type / Status
Subject Five Lakes Region E332140 entity
Predicate hasPart P35 FINISHED
Object Starnberger See E41860 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: Starnberger See | Statement: [Five Lakes Region, hasPart, Starnberger See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starnberger See
Context triple: [Five Lakes Region, hasPart, Starnberger See]
  • A. Starnberger See chosen
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • B. 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.
  • C. Ammersee
    Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
  • D. Schliersee
    Schliersee is a picturesque lake and town in the Bavarian Alps of southern Germany, known for its scenic mountain setting and outdoor recreation.
  • E. Scharmützelsee
    Scharmützelsee is a popular lake in eastern Germany known for its scenic surroundings, recreational activities, and spa resorts.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0284428081908043c55caeefb833 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fba1ba309c81908d83ba7efc663787 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 10:12 p.m.