Triple

T21826719
Position Surface form Disambiguated ID Type / Status
Subject Christian Daniel Rauch E538873 entity
Predicate placeOfBirth P1 FINISHED
Object Arolsen NE NERFINISHED

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: Arolsen | Statement: [Christian Daniel Rauch, placeOfBirth, Arolsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arolsen
Context triple: [Christian Daniel Rauch, placeOfBirth, Arolsen]
  • A. Arolsen chosen
    Arolsen is a historic town in the German state of Hesse, known for its baroque architecture and as the former residence of the princes of Waldeck and Pyrmont.
  • B. Buchenwald
    Buchenwald was one of Nazi Germany’s largest and most notorious concentration camps, where tens of thousands of prisoners were subjected to forced labor, brutal conditions, and mass murder during the Holocaust.
  • C. Anhausen
    Anhausen is a small German village best known as the birthplace of professional golfer Bernhard Langer.
  • D. Dachau
    Dachau was one of Nazi Germany’s first and most infamous concentration camps, serving as a model for the camp system and a site of widespread persecution, forced labor, and mass murder during the Holocaust.
  • E. Geisenhausen
    Geisenhausen is a market town in Lower Bavaria, Germany, known for its rural character and proximity to the city of Landshut.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475038c8190abb9b1a20eb8ff50 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f09132ae888190b8c1a8e75b96b5fd completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:54 p.m.