Triple

T14379955
Position Surface form Disambiguated ID Type / Status
Subject Johann Franz Encke E356573 entity
Predicate placeOfDeath P21 FINISHED
Object Spandau E78225 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: Spandau | Statement: [Johann Franz Encke, placeOfDeath, Spandau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spandau
Context triple: [Johann Franz Encke, placeOfDeath, Spandau]
  • A. Spandau chosen
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • B. Sachsenhausen
    Sachsenhausen is a district or neighborhood within the town of Giengen an der Brenz in the German state of Baden-Württemberg.
  • C. Sachsenhausen
    Sachsenhausen is a historic and culturally vibrant district of Frankfurt am Main, known for its traditional apple wine taverns, museums, and picturesque old town streets.
  • D. Berlin-Moabit
    Berlin-Moabit is a central Berlin neighborhood known for its industrial heritage, diverse population, and proximity to major transport and government districts.
  • E. Charlottenburg
    Charlottenburg is a historic district in western Berlin, Germany, known for its baroque Charlottenburg Palace and role as a former independent city before incorporation into Berlin.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cd3aa20819089c8527faf1ceddd completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:16 a.m.