Triple

T8399994
Position Surface form Disambiguated ID Type / Status
Subject Bauhaus school of design E198147 entity
Predicate location P40 FINISHED
Object Dessau E102721 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: Dessau | Statement: [Bauhaus school of design, location, Dessau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau
Context triple: [Bauhaus school of design, location, Dessau]
  • A. Dessau chosen
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • B. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • C. Degendorf
    Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
  • D. Sangerhausen
    Sangerhausen is a town in the German state of Saxony-Anhalt, known for its historic mining heritage and its renowned Europa-Rosarium rose garden.
  • E. Zerbst
    Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb824bfcbc8190b26bfcb5f8c4777c completed March 31, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb70fbf881909daefb3162ba803c completed April 3, 2026, 3:23 p.m.
Created at: March 30, 2026, 6:04 p.m.