Triple

T9350315
Position Surface form Disambiguated ID Type / Status
Subject Würmsee E224998 entity
Predicate alternativeName P39 FINISHED
Object Wurmsee E224998 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: Wurmsee | Statement: [Würmsee, alternativeName, Wurmsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wurmsee
Context triple: [Würmsee, alternativeName, Wurmsee]
  • A. Würmsee chosen
    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.
  • B. Rothsee
    Rothsee is an artificial recreational lake in Middle Franconia, Bavaria, popular for swimming, sailing, and other water sports.
  • C. Ziegelsee
    Ziegelsee is a lake in the city of Schwerin in northern Germany, known for its scenic waterfront and role in the region’s interconnected lake system.
  • D. Weissensee
    Weissensee is a picturesque alpine lake and surrounding region in southern Austria, renowned for its clear waters, outdoor recreation, and unspoiled natural landscape.
  • E. Waginger See
    Waginger See is a warm, scenic lake in southeastern Bavaria, Germany, popular for swimming, water sports, and tourism in the Chiemgau region.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f9248c08190a7bb40feec2eb217 completed April 1, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d74fa545b8819092809c605542476a completed April 9, 2026, 7:05 a.m.
Created at: March 30, 2026, 7:41 p.m.