Triple

T8771790
Position Surface form Disambiguated ID Type / Status
Subject Schwanstein Castle E208479 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: [Schwanstein Castle, overlooks, Schwansee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwansee
Context triple: [Schwanstein 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. Tachinger See
    Tachinger See is a small scenic lake in the Chiemgau region of Bavaria, Germany, known for swimming, fishing, and its tranquil natural surroundings.
  • C. Gebesee
    Gebesee is a small town in the German state of Thuringia, situated near the confluence of the Unstrut and Gera rivers and known for its agricultural surroundings.
  • D. Stadtsee
    Stadtsee is a small lake located in the town of Bad Waldsee in southern Germany, known for its scenic setting and recreational use.
  • E. Plau am See
    Plau am See is a small town and lakeside resort in the Mecklenburg Lake District of northern Germany, known for its natural scenery and water-based recreation.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2c54c08190a904723d1f0527a4 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14bb716cc819096a1e02e61db2e69 completed April 4, 2026, 5:34 p.m.
Created at: March 30, 2026, 6:41 p.m.