Triple

T19592508
Position Surface form Disambiguated ID Type / Status
Subject Luiseninsel E470270 entity
Predicate locatedIn P40 FINISHED
Object Mitte, Berlin 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: Mitte, Berlin | Statement: [Luiseninsel, locatedIn, Mitte, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitte, Berlin
Context triple: [Luiseninsel, locatedIn, Mitte, Berlin]
  • A. Mitte, Berlin chosen
    Mitte, Berlin is the central district of Germany’s capital city, known for its historic core, major cultural institutions, and many of Berlin’s most famous landmarks.
  • B. Mitte (Leipzig)
    Mitte (Leipzig) is the central district of Leipzig, Germany, encompassing the historic city center and key cultural and administrative landmarks.
  • C. Berlin Gesundbrunnen
    Berlin Gesundbrunnen is a major railway and transport hub in northern Berlin, serving regional, long-distance, and S-Bahn trains as well as local U-Bahn and bus connections.
  • D. Friedrichswerder, Berlin
    Friedrichswerder is a historic inner-city quarter of Berlin known for its 19th-century architecture and cultural landmarks near the city’s political and museum districts.
  • E. Berlin government district
    The Berlin government district is the central area of Germany’s capital that houses key federal institutions, including the Bundestag in the Reichstag building and the offices of the Chancellor.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64057460c8190962e2e58f06b3985 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:43 p.m.