Triple

T14445339
Position Surface form Disambiguated ID Type / Status
Subject Dietrich Eckart E358190 entity
Predicate placeOfDeath P21 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: [Dietrich Eckart, placeOfDeath, Berchtesgaden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berchtesgaden
Context triple: [Dietrich Eckart, placeOfDeath, 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. Reichenhall
    Reichenhall is a Bavarian spa town in southeastern Germany, renowned for its salt springs and alpine setting.
  • C. Garmisch-Partenkirchen
    Garmisch-Partenkirchen is a renowned Bavarian alpine town in southern Germany, famous for skiing, winter sports, and its picturesque mountain scenery.
  • D. Mulchén
    Mulchén is a Chilean city located in the Biobío Region, known historically for its forestry-based economy and role in the country’s south-central development.
  • E. Freilassing
    Freilassing is a Bavarian town in southeastern Germany near the Austrian border, known as a key railway junction and gateway to the city of Salzburg.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de915e76f481909fe9462f964b5b1c completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bdd0f388190870ddd01f66d3e99 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:19 a.m.