Triple

T4552677
Position Surface form Disambiguated ID Type / Status
Subject Untersberg E120402 entity
Predicate near P350 FINISHED
Object Berchtesgaden E45384 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: Berchtesgaden | Statement: [Untersberg, near, Berchtesgaden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berchtesgaden
Context triple: [Untersberg, near, Berchtesgaden]
  • A. Berchtesgaden chosen
    Berchtesgaden is a picturesque alpine town in southeastern Bavaria, Germany, known for its dramatic mountain scenery, historical ties to the Nazi era, and proximity to the Eagle’s Nest and Berchtesgaden National Park.
  • B. Garmisch-Partenkirchen
    Garmisch-Partenkirchen is a renowned Bavarian alpine town in southern Germany, famous for skiing, winter sports, and its picturesque mountain scenery.
  • C. Seiffen
    Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
  • D. Igls
    Igls is an Austrian alpine village near Innsbruck known for its winter sports facilities and role in hosting Olympic events.
  • E. Olbernhau
    Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd581160e08190b715a8ce5c3e6c9b completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb95b01b0819094a600752e41aa09 completed March 20, 2026, 9:17 p.m.
Created at: March 20, 2026, 1:09 p.m.