Triple

T10948752
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Lichterfelde archive site E258668 entity
Predicate locatedIn P40 FINISHED
Object Lichterfelde E208659 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: Lichterfelde | Statement: [Berlin-Lichterfelde archive site, locatedIn, Lichterfelde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichterfelde
Context triple: [Berlin-Lichterfelde archive site, locatedIn, Lichterfelde]
  • A. Lichterfelde chosen
    Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
  • B. Mahlsdorf
    Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
  • C. Wandlitz
    Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
  • D. Degendorf
    Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
  • E. Ludwigsfelde
    Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ec7028819084f5ce2035a128e4 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e374226b6081909c8db367e7d468a5 completed April 18, 2026, 12:08 p.m.
Created at: April 8, 2026, 9:23 p.m.