Triple

T1848292
Position Surface form Disambiguated ID Type / Status
Subject Hohenschwangau Castle E41333 entity
Predicate overlooks P1323 FINISHED
Object Schwansee E215122 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: Schwansee | Statement: [Hohenschwangau Castle, overlooks, Schwansee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwansee
Context triple: [Hohenschwangau Castle, overlooks, Schwansee]
  • A. Schwansee chosen
    Schwansee is a picturesque alpine lake in Bavaria, Germany, known for its scenic setting near Neuschwanstein and Hohenschwangau castles.
  • B. Schluchsee
    Schluchsee is a large reservoir and popular recreational lake in Germany’s Black Forest, known for swimming, sailing, and scenic hiking.
  • C. Schlachtensee
    Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
  • D. Rummelsburger See
    Rummelsburger See is a small inner-city lake and former industrial harbor basin in Berlin, Germany, known today for its residential waterfront and recreational areas.
  • E. Maschsee
    Maschsee is an artificial lake and popular recreational area in Hanover, Germany, known for boating, walking paths, and cultural events.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb05412a08190855ea453d1264ea3 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0abb346081908df2c8390e4938d5 completed March 8, 2026, 11:48 p.m.
Created at: March 4, 2026, 7:33 p.m.