Triple

T7181290
Position Surface form Disambiguated ID Type / Status
Subject Friedrich Albert Lange E167452 entity
Predicate placeOfDeath P21 FINISHED
Object Marburg E174796 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: Marburg | Statement: [Friedrich Albert Lange, placeOfDeath, Marburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marburg
Context triple: [Friedrich Albert Lange, placeOfDeath, Marburg]
  • A. Marburg chosen
    Marburg is a historic university town in central Germany known for its well-preserved medieval old town and the Philipps-Universität, one of the oldest Protestant universities in the world.
  • B. Vienenburg
    Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
  • C. Riemst
    Riemst is a municipality in the Belgian province of Limburg, known for its rural character and location near the borders with the Netherlands and Germany.
  • D. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • E. Neustadt
    Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8bc25088190a7d7f3ba2461b5e9 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b93d04ec8190ac5c5bf9ace7eca1 completed March 28, 2026, 11:19 a.m.
Created at: March 27, 2026, 2:49 p.m.