Triple

T8556070
Position Surface form Disambiguated ID Type / Status
Subject Anni Albers E202565 entity
Predicate workLocation P7 FINISHED
Object Dessau, Germany 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, Germany | Statement: [Anni Albers, workLocation, Dessau, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau, Germany
Context triple: [Anni Albers, workLocation, Dessau, Germany]
  • A. Friedberg, Germany
    Friedberg, Germany is a historic town in the state of Hesse known for its medieval architecture, including a well-preserved castle and old town center.
  • B. Schröttinghausen, Germany
    Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
  • C. Dessau chosen
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • D. Brühl, Germany
    Brühl, Germany is a town in North Rhine-Westphalia known for its UNESCO-listed Augustusburg and Falkenlust palaces and its proximity to Cologne.
  • E. Frohnhausen, Germany
    Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
  • 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_69ca832610e08190b3b6c6cd2c250255 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe88bcce081909e12e4037a0e6323 completed March 31, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce893b24c0819094fead15749fe1ee completed April 2, 2026, 3:20 p.m.
Created at: March 30, 2026, 6:19 p.m.